Urban Governance 3 (2023) 228–242 Contents lists available at ScienceDirect Urban Governance journal homepage: www.elsevier.com/locate/ugj The moderating role of Covid-19-related support on urban livelihood capitals: Evidence from suburban Accra Seth Asare Okyerea, b , Louis Kusi Frimpongc, ∗ , Matthew Abunyewahd ,e , Stephen Kofi Diko f, Md. Nawrose Fatemig, Stephen Leonard Mensahh , Seth Barnie Enningh, Michihiro Kitab a School of Landscape Architecture and Planning, University of Arizona, USA b Graduate School of Engineering, Osaka University, Japan c Department of Geography and Earth Science, University of Environment and Sustainable Development, PMB, Somanya, Eastern Region, EY0329 ‐2478, Somanya, Ghana d School of Architecture and Built Environment, University of Newcastle, Australia e The Australasian Centre for Resilience Implementation for Sustainable Communities, Charles Darwin University, Australia f Department of City and Regional Planning, University of Memphis, USA g Department of Architecture, University of Asia Pacific (UAP), Dhaka, Bangladesh h Department of Geography and Resource Development, University of Ghana, Ghana a r t i c l e i n f o a b s t r a c t Keywords: In the Global South, the COVID-19 crisis has compelled varied efforts to quickly address the pandemic’s impact COVID-19 impact on urban livelihoods. Families, friends as well as public, private, and civil society organizations have mobilized Urban livelihoods various resources to avert the pandemic’s onslaught on the survival of the urban vulnerable. Indeed, there is a Covid-19-related support burgeoning ‘pandemic urban scholarship’ that shed insights on COVID-19 risks, local responses, and impacts on Structural equation modelling everyday urban life. Yet, it is unclear how many of these responses are affecting urban livelihoods. This paper Post-pandemic resilience thus investigates the impact of COVID-19 on urban livelihood capitals (financial, human, social, and physical) and analyses the moderating role of COVID-19-related support (from families, friends, government agencies, faith-based and non-governmental organizations) to address the pandemic’s impact on these capitals. Drawing on a quantitative study in Adenta Municipality of the Greater Accra Region, Ghana, the study finds a negative association between COVID-19 impacts and all urban livelihood capitals. Crucially, COVID-19-related support only reduced the negative impact of the pandemic on financial capital, and not on the other forms of capital. The study suggests that building post-pandemic community resilience warrants the need to transition from the usual reactive, fragmented support to integrated, holistic, and contextually embedded long-term strategies that consider the multi-dimensionality of everyday urban life. 1 p S c ( l A w w l c s p c d t m m i a h R A 2 l . Introduction We know how to bring the economy back to life. What we do not know is how to bring people back to life. We will, therefore, protect people’s lives, then their livelihoods. (President Nana Addo-Dankwa Akufo-Addo) The COVID-19 pandemic has emerged as both a global health and ivelihood threat with localised impacts and disruptions to the socio- patial and economic aspects of everyday urban life. In Global South ontexts, the pandemic hastened early warnings from the international evelopment and scholarly community to national and local govern- ents and their development partners to address existing vulnerabil- ties and develop robust responses to improve fragile livelihoods and∗ Corresponding author. E-mail address: lkfrimpong@uesd.edu.gh (L. Frimpong) . ttps://doi.org/10.1016/j.ugj.2023.03.003 eceived 24 May 2022; Received in revised form 20 February 2023; Accepted 16 Ma vailable online 30 March 2023 664-3286/© 2023 The Author(s). Published by Elsevier B.V. on behalf of Shanghai icense ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ) recarious living conditions of the urban vulnerable ( Balde et al., 2020 ; mit, 2020 ; UN-Habitat, 2020 ). In sub-Saharan Africa (SSA), capital ities gradually became the epidemiological loci of the COVID-19 virus UN-Habitat, 2020 ) as well as the hotspots of its impacts on everyday ivelihoods. In particular, the pervasiveness of the informal sector in frican urbanism ( Okyere & Kita, 2015 ; Okyere et al., 2021 ), coupled ith structural challenges in urban governance and service provision, eak planning systems, and persistent socio-economic vulnerabilities ompounded the pandemic impact across social, economic, spatial, and olitical aspects of urban life ( Asante & Mills, 2020 ). Across SSA, weak fiscal capacity to support local economies to limit he impacts of the COVID-19 pandemic on urban livelihoods remains a ajor source of concern ( Visagie & Turok, 2021 ). Already, impacts such s job losses and declines in wage earnings, disrupted social networks,rch 2023 Jiao Tong University. This is an open access article under the CC BY-NC-ND S. Okyere, L. Frimpong, M. Abunyewah et al. Urban Governance 3 (2023) 228–242 e e i t A i & a Z b s b n a d d n t e t C p a s t D b e h ( h e fi i t c v ( a i t T c t t g d b a C 1 t r i T m r 2 h t a h t f S o 2 c a r i r d & C p t l t d w r A p h a s t H i p h r m W s b r ( r p s c w h H d c r i 2 i d o 2 g h e a m P rosion of informal insurance mechanisms, business closures, and food nsecurity have been reported in major African cities such as Cape Town, ccra, Addis Ababa, Lagos, and Kampala ( Asante & Mills, 2020 ; Ojogiwa Akinola, 2020 ; Bukuluki et al., 2020 ; Aragie et al., 2021 ; Schotte & izzamia, 2021 ). Cognizant of these impacts and the risk they pose to the ustainability of urban life (see Section 1 headline quote), various SSA ational governments transitioned from or combined disciplinary lock- owns with mass risk information campaigns, distribution of everyday ecessities and cash handouts (relief packages) to support those consid- red highly vulnerable. South Africa, for example, introduced special OVID-19 Social Relief of Distress grant estimated to have benefited bout 4-5 million people ( Visagie & Turok, 2021 ). Other support ini- iatives were introduced by governments such as the waiver of utility ills in Ghana ( Gbedemah et al., 2022 ; Akrofi & Antwi, 2020 ) and cash andouts in Sierra Leone ( Osuteye et al., 2020 ). Correspondingly, these efforts have caught the attention of south- rn urban scholars, where burgeoning ‘pandemic urban scholarship’ n Africa has ensued, shedding insightful commentaries and criti- al analyses on entrenched vulnerabilities that foster COVID-19 risks Smit, 2020 ), multi-scalar responses ( Frimpong et al., 2022 ) and emerg- ng impacts on people and places ( Bukuluki et al., 2020 ; Visagie & urok, 2021 ). While useful, the emerging scholarship is yet to attend to he role the varied support residents received from families, friends, non- overnmental organizations (NGOs), government agencies, and faith- ased organizations (FBOs), among others —hereafter referred to as OVID-19-related support — played in moderating the relationships be- ween COVID-19 impacts and urban livelihoods. In other words, as the mplications of COVID-19 ′ s impact on urban livelihoods are gaining mo- entum ( Asante & Mills, 2020 ; Kansiime et al., 2021 ; Shupler et al., 021 ), an important question emerges: do COVID-19-related support help ackle the pandemic’s impact on urban livelihoods? This paper attempts to respond to this question and thus contribute o the emerging literature on the pandemic in urban SSA. It draws on tructural Equation Modelling (SEM) to analyze the moderating role f COVID-19-related support on COVID-19 impacts on urban livelihood apitals in Adenta Municipality of the Greater Accra Region in Ghana — hotspot of COVID-19 crises, impacts and responses. The moderating ole concerns how COVID-19-related support changes the strength of the elationships between COVID-19 impacts and urban livelihoods ( Sauer Dick, 1993 ; Hair, 2021). In other words, does COVID-19-related sup- ort reduce the negative impact of the COVID-19 pandemic on urban ivelihood capitals? This paper’s emphasis on moderation, instead of a irect relationship, is context-specific, given the reality that COVID-19- elated support programs were aimed at cushioning households to im- rove their livelihood conditions rather than directly eradicating neg- tive impacts. The paper’s contributions are threefold: (i) it establishes he relationship between COVID-19 and specific forms of livelihood cap- tals —social, financial, human, and physical — that define urban liveli- oods, extending current generalised framings (see Schotte & Zizza- ia 2021 ); (ii) it brings to the fore the performance of COVID-19-related upport across different forms of capitals, extricating missing links and aising concerns about the dangers of fragmented and reactive pandemic esponse and (iii) provides pointers to practitioners on the need for in- titutionalization of coordinated, integrated, holistic, and place-aware elfare initiatives that speak to the multidimensionality of urban liveli- oods (see Okyere et al. 2021 ; Visagie & Turok 2021 ) as part of the iscourse on engendering resilient people and places. The next section eviews related literature on health pandemics to develop the hypothet- cal relationships between COVID-19 impacts and urban livelihood cap- tals. The study setting follows in Section 3 . The study methods, results, iscussion, and conclusion then proceed respectively. . Health pandemics and urban livelihood capitals: a review and ypothesis Health pandemics exert a significant impact on urban livelihoods in ulti-scalar and complex ways. While health pandemics are considered229 xogenous shocks and thus global ( Callegari & Feder, 2021 ), their ex- ent and severity can be localized depending on endogenous factors that nform local resilience systems. This paper is underpinned by Chambers nd Conway’s notion that “a livelihood comprises people, their capa- ilities and their means of living including food, income, assets. Tangi- le assets are resources and stores, and intangible assets are claims and ccess. ” ( Chambers & Conway, 1992 , (ii). Livelihoods thus enable resi- ents to recover from varied forms of stress and shocks and support them o maintain or improve their capabilities and assets in the present and fu- ure. This understanding has inspired several sustainable livelihood ap- roaches ( Carney et al., 1999 ). One of these approaches, employed with ome variation by this paper, is the UK’s Department for International evelopment (DFID) sustainable livelihood framework, which was mod- led after Chambers and Conway’s conceptualization of a livelihood Carney et al. 1999 ). While the DFID’s framework emphasizes five liveli- ood capitals ( DFID, 1999 ), this paper emphasizes four capitals namely: nancial, social, human, and physical capital —excluding natural capi- al because of the urban context of this study. From this framework, our ulnerability context is the COVID-19 pandemic which created shocks nd stresses in Ghana’s urban environments. The livelihoods comprise he capitals which is the range of assets (either owned or accessed) to ope with or recover from the COVID-19 pandemic. Transforming struc- ures and processes comprises the COVID-19-related support that resi- ents received either from families and friends, the government, NGOs, nd FBOs that enabled them to cope with and recover from the COVID- 9 pandemic. The livelihood strategies are the specific actions taken by esidents to tackle the impacts of the COVID-19 pandemic on their lives. ogether with COVID-19-related support, it is expected that these would educe the negative impact of the COVID-19 pandemic on urban liveli- ood capitals ( Fig. 1 ). Following this section, we draw on the literature nd the sustainable livelihood framework to further elucidate the eight ypotheses that inform the structural equation model ( Fig. 2 ) developed or this study. .1. Relationship between health pandemics and financial capital Financial capital is the financial resources such as savings, cred- ts, remittances, income, etc. that are available to and enable resi- ents to acquire and provide different goods and services ( DFID, 1999 , arney et al., 1999 ). Health pandemics often stifle economic activi- ies that enable residents to develop their financial capital. They tend o increase health care costs, reduce savings and capital accumulation hich negatively affect residents’ financial capital ( Asegie et al., 2021 ). lthough pandemic shocks are heterogeneous among sectors such as ealth, retail, transport, and tourism ( Mahal, 2004 ; Verikios, 2020 ), tudies confirm that in SSA, long-lived pandemics such as malaria and IV/AIDS cause physical weakness which in turn reduce income ca- acity, deplete savings, and worsen credit availability for households — einforcing existing poverty traps ( Gallup & Sachs, 2001 ; Gustafsson- right et al., 2011 ). In impoverished settings, pandemics also exacer- ate inequities in the financial holdings of lower socio-economic groups Gustafsson-Wright et al., 2011 ). From these observations, the study hy- othesizes that the COVID-19 pandemic negatively impacts financial apital. 1. COVID-19 pandemic impact has a negative relationship with finan- ial capital .2. Relationship between health pandemics and human capital Human capital refers to knowledge, skills, training, abilities, and ther characteristics people possess and use in the production of oods and services ( Carney et al., 1999 ; DFID, 1999 ). The extant lit- rature indicates a negative relationship between health pandemics nd human capital ( Callegari & Feder, 2021 ; Zinyemba et al., 2020 ). ercoco (2016) revealed that the outbreak of the Spanish flu reduced S. Okyere, L. Frimpong, M. Abunyewah et al. Urban Governance 3 (2023) 228–242 Fig. 1. Sustainable Urban Livelihood Framework on the COVID-19 pandemic. Source: Developed with inspiration from the DFID’s Sustainable Livelihood Framework (see Carney et al. 1999 ; DFID 1999 ) Fig. 2. A Conceptualization of the Structural Equation Model and Hypotheses. t 2 t l a p H s m h e 2 W a p n i p a M l d u c he average years of schooling in Italian regions and generated a persis- ent effect on human capital accumulation for those born between 1918 nd 1920. In low-income settings of global south communities where overty traps are rampant, studies have shown that previous pandemics uch as HIV/AIDS and Poliomyelitis affected individuals and house- olds’ abilities to improve health conditions and access to productive mployment, thereby reducing long-term human capital ( Gustafsson- right et al., 2011 ). Health pandemic impacts are also evident in trade nd business activities, especially when Small and Medium Scale Enter- rises (SMEs) are unable to operate normally and thus struggle to invest n their employees ( Okediya, 2020 ). Consequently, personnel may be ffected by unmanageable health care issues, unpaid allowances, job oss, and disruptions to children’s schooling. Given that such pandemic ncertainties affect investments in intangible capital ( Lorentzen et al.,230 008 ), we hypothesize that the COVID-19 pandemic has a negative re- ationship with human capital. 2. COVID-19 pandemic impact has a negative relationship with hu- an capital. .3. Relationship between health pandemics and social capital Social capital typically encompasses networks and the social chan- els that support the flow of essential resources to sustain and sup- ort livelihoods in crisis situations ( Carney et al., 1999 ; DFID, 1999 ; orsut et al., 2022 ). However, scholars have noted that health pan- emics impede social capital accumulation due to reduced social ommunication, community networks and interpersonal relationships, S. Okyere, L. Frimpong, M. Abunyewah et al. Urban Governance 3 (2023) 228–242 e o K t o h t o e m c c c r e h h t c C ( l m i ( t c t K a p fi 1 l t a t v H t c i T 2 f s w t D s s p i 1 i t a ( 2 o t A p t a a K 2 t h t 2 p C a s p c G C a fi 2 p v o t i t r C H o i w 2 p p I t p p o l 2 s C t p a p N p a t G H A tspecially in low-income settings ( Makridis & Wu, 2021 ; Wong & ohler, 2020 ). During the Ebola epidemic in Liberia, for example, fear f direct transmission of the Ebola virus restricted everyday social prac- ices and rituals (e.g., handshaking, hosting family and friends and social vents), limited access to social networks, eventually forestalling social apital accumulation ( Alonge et al., 2019 ). Such limited access to so- ial networks often results in mistrust, fear, and psychological trauma, specially in urban informal settlements ( Alonge et al., 2019 ). Indeed, ealth epidemics and pandemics disrupt social capital but also generate ascading effects in long-term economic, social, and cultural dimensions Aassve et al., 2020 ). Yet, social networks and resources within com- unities are essential for coping and recovering from crises situations Alonge et al., 2019 ; Fatemi et al., 2020 ; Abunyewah et al., 2022 ), in- luding health pandemics ( Frimpong et al., 2022 ; Alfano, 2022 ; Wong & ohler, 2020 ). Nonetheless, this study hypothesizes that the COVID-19 andemic negatively impacts social capital given the nature of COVID- 9 pandemic policies such as social distancing, post-exposure quaran- ining, shelter-in-place orders, and travel bans that restricted movement nd interactions. 3. COVID-19 pandemic impact has a negative relationship with social apital. .4. Relationship between health pandemics and physical capital Physical capital in this study refers to tangible (e.g., lands, proper- ies, tools) and non-human assets or basic infrastructure (e.g., hospitals, chools, community centers, recreational sites and amenities) to sup- ort health, education, recreation and leisure activities ( Carney et al., 999 ; DFID, 1999 ; Ulya et al. 2021 ). A recent systematic review found hat health pandemics have a negative relationship with physical capital Callegari & Feder, 2021 ). In SSA, scholars have emphasized the impact f health pandemics ( Masanjala, 2007 ; Hunter et al., 2011 ; Bhandari & longe, 2020 ) on physical capital degradation, highlighting the sequen- ial loss of and disposal of assets such as land, equipment and domestic nimals. For instance, during the Ebola epidemic in Liberia ( Gatisoet al., 018 ; McQuilkin et al., 2017 ) and Guinea ( Delamou et al., 2017 ), restric- ions on domestic and international travel were imposed, resulting in he complete closure of schools and markets, which significantly ham- ered the livelihoods of individuals and households by limiting their ccess to various livelihood assets. This persisted during the COVID-19 andemic where, for instance, school closures persisted for months in hana ( Wolf et al., 2022 ). Moreover, the Ebola outbreak disproportion- tely affected recreation sites and tourist destinations ( Nsoesie et al., 015 ), with visitors cancelling trips to parts of the SSA region where the irus had not been detected ( Maphanga & Henama, 2019 ). In view of his understanding, we hypothesize that COVID-19 negatively impacts he utilization of physical capital. 4. COVID-19 pandemic impact has a negative relationship with phys- cal capital. .5. Role of COVID-19-related support during health pandemics Wilkinson (2020) suggests that health pandemics control methods end to be ineffective unless the social and livelihood implications are roperly considered. At a broader level, the ensuing scholarship out- ined above suggests that health pandemics have a negative relation- hip with the various capitals —financial, human, social and physical — hat compose urban livelihoods. Nevertheless, a strand of the literature lso posits that support from families, friends, government agencies, GOs, FBOs, and CSOs, among others (e.g., safety nets, cash handouts, nd food supplies), can potentially weaken the negative relationship be- ween health pandemics and urban livelihood capitals ( Aber et al., 2021 ; reyling et al., 2016 ; Devereux, 2021 ; Ali et al., 2022 ). For instance, longe et al. (2019) report that community-based groups’ facilitation231 f information dissemination and exchange of economic resources con- ributed to reducing the impact of the Ebola epidemic on the financial, uman, and physical capital of vulnerable communities in Liberia. More- ver, Alonge et al. (2019) and Frimpong et al. (2022) share the view that ultisectoral actors, including governments, NGOs, FBOs, and CSOs, an help restore weakened social networks and build better bonds to eignite collective action necessary for social capital accumulation amid ealth crises. However, these are dependent on the effective collabora- ion among different levels of actors involved in the implementation of OVID-19-related support to assuage its adverse impacts on residents’ ivelihoods ( Frimpong et al., 2022 ). A review of support provided dur- ng health pandemics in multiple SSA countries found that food and cash ransfers, micro-credit initiatives, and psychosocial support by interna- ional, national, and local agencies contributed to weakening the neg- tive impacts of health disasters on residents by cushioning residents’ nancial, human and social capitals at the individual and household evels ( Aberman et al., 2014 ; Devereux, 2021 ). Indeed, both COVID-19 impacts and government movement restric- ions to curtail transmissions ( Brauner et al., 2021 ) occasioned ad- erse livelihood impacts on residents. As a result, governments around he world implemented varied support interventions to help their res- dents assuage these impacts ( Devereux, 2021 ; OECD, 2021 ; Visagie & urok, 2021 ; Akrofi & Antwi, 2020 ; Osuteye et al., 2020 ). Family and riends as well as NGOs and FBOs also provided financial and material upport to residents ( Cloulaud et al., 2023 ; Gill 2022). However, these ere not without challenges. Some studies ( Fakhruddin et al., 2020 ; aszak et al., 2021 ; Schmidt-Sane et al., 2021 ; Devereux, 2021 ), for in- tance, note how COVID-19 related support interventions were limited n scope and ad-hoc. Funding of NGOs and governments for humanitar- an efforts also declined reducing their capacity to provide consistent nd holistic support to residents ( Lone & Ahmad, 2020 ; Wilke et al., 020 ; Asogwa et al., 2022 ). Bisong et al. (2020) also noted how remit- ances from families and friends declined during the peak periods of the andemic. In some cases, efforts to restrict transmission meant limited ccess to support from families and friends ( Yu et al., 2021 ; Wong & ohler, 2020 ). Moderation analysis through structural equation modeling can elp understand the influence of interventions ( Anwar et al., 020 ; Seow et al., 2021 ; Hair et al., 2021 ). For instance, oulaud et al (2023) using moderation analysis found that financial upport from family and friends moderated the negative effect of in- ome loss resulting from the COVID-19 pandemic. Gill et al. (2022) and oulaud et al., (2023) emphasize how the nature and delivery mode of nancial support influence the moderating roles of support during the andemic. Furthermore, COVID-19-related supports only forms part f the factors influencing the degree to which COVID-19 pandemic mpacts residents ( Coulaud et al., 2023 ). This illustrate how COVID-19- elated support is another factor influencing the relationship between OVID-19 impacts and livelihood capital. Herein lies the importance f moderation analysis understanding how COVID-19-related support eakens COVID-19 impacts on livelihoods. Therefore, we hypothesize that COVID-19-related support during andemics weakens the negative relationship between COVID-19 im- act and livelihood capitals (financial, social, human and physical). n other words, COVID-19-related supports reduces the negative im- acts of the COVID-19 pandemic on urban livelihood capitals. Based n the moderation literature ( Aberman et al., 2014 ; Anwar et al., 020 ; Devereux, 2021 ; Seow et al., 2021 ; Hair et al., 2021 ; Gill 2022; loulaud et al., 2023 ), and the objective of the COVID-19-related sup- ort initiatives in the study context ( Ministry of Finance, 2020 ), this aper sought to examine the moderating role of COVID-19 related sup- ort instead of its direct effects. 5. COVID-19-related support weakens the negative relationship be- ween the COVID-19 pandemic impact and financial capital S. Okyere, L. Frimpong, M. Abunyewah et al. Urban Governance 3 (2023) 228–242 Fig. 4. Regional distribution of COVID-19 reported cases as of February 14, Fig. 3. Ghana’s COVID-19 reported cases between March 2020 and March 2022 2022 (Source: Our World in Data). (Our World in Data, 2022). a H f t t i H t i i H s t t d 3 ( i t h a t o t e a f n ( v a i ( a t t G l g t 2 t f S h o h t l e s P l t b n ( ( a g e c h C d 2 r m C m a w h w s c t i c t I g A w t f r i c r T m 1 6. COVID-19-related support weakens the negative relationship be- ween the COVID-19 pandemic impact and social capital 7. COVID-19-related support weakens the negative relationship be- ween the COVID-19 pandemic impact and human capital 8. COVID-19-related support weakens the negative relationship be- ween the COVID-19 pandemic impact and physical capital . Profiling greater Accra within the COVID-19 outbreak: cases, mpacts and responses Accra, the capital of Ghana has witnessed a significant transforma- ion, both demographically and spatially over the years. A combination f factors such as migration, net-natural increase, the concentration of conomic activities, and interaction with the international market has acilitated this transformation, making it the dominant city in Ghana Grant, 2009 ; Owusu & Oteng-Ababio, 2015 ). Accra has developed into functional area, which is called the Greater Accra Metropolitan Area GAMA). The population of GAMA is about 5.4 million ( Ghana Statis- ical Service (GSS), 2021 ), making it the largest metropolitan area in hana. Accra’s growth has been accompanied by poor planning, slug- ish economic growth, and widening income inequalities ( Okyere et al., 021 ). This situation has increased household vulnerabilities to various orms of hazards, including environmental health hazards. Many house- olds face health problems in Accra, owing to numerous environmental ealth risks in the city. However, the ability to deal with the accumu- ated health risk in Accra depends on where a person resides and their ocio-economic status ( Weeks et al., 2013 ). Poor urban communities iving either close to the city center or in suburban areas of the city ear a disproportionate share of the major disease burden in the city Verutes et al., 2012 ; Weeks et al., 2012 ), and are the least to cope with nd recover from diseases and other health shocks. The nexus between the health and socio-economic dynamics of Ac- ra has become an important subject of discussion during this period of OVID-19. Ghana recorded its first two cases of COVID-19 on March 12, 020 —and months after, the country recorded more cases, with com- unity spread being the major contributing factor. Fig. 3 shows the onthly reported cases for the country from March 2020 to March 2022, ith the highest number of reported cases per month being June 2020, hich was just three months after the first two cases. The number of onfirmed cases dropped for the next six months and increased signif- cantly in February 2021. There was a drop-in case after February and hen picked up again in August 2021 and December 2021 respectively. n terms of the regional distribution, as of February 14, 2022, Greater ccra had 88,206 reported cases of COVID-19, constituting 59% of the otal national reported cases since March 12, 2020. Fig. 4 shows the egional distribution of COVID-19 cases in Ghana. The impacts of COVID-19 on Ghana’s economy have been far- eaching as a result of the partial lockdown (April to June 2020) in its ajor cities of Accra and Kumasi, leading to the halt of major economic232 ctivities. For instance, it was reported that approximately 36% of in- ormal businesses were closed during the partial lockdown which led o about 90% of formal and informal businesses reporting a reduction n sales ( GSS, 2020 ). Particularly in Accra, the lockdown led to a sharp ncrease in the prices of foodstuff and essential commodities due to lim- ted import and supply from local producers, and panic buying from con- umers ( Asante & Mills, 2020 ). Owners of informal businesses, especially hose engaged in home-based enterprises, were hard hit by the lock- own leading to worsening economic conditions for many households Aduhene & Osei-Assibey, 2021 ). Indeed, Bukari et al. (2021) found that he COVID-19 pandemic significantly increased the poverty levels of ouseholds and reduced household consumption for those in the middle nd upper-income groups in Ghanaian cities. To reduce the impact of COVID-19 on the populace and revitalize he urban economy, the government introduced several interventions imed at assisting poor households, as well as formal and informal busi- esses. For instance, the government, in collaboration with FBOs, pro- ided free food and other essential commodities to poor households n Accra during the lockdown ( Dadzie & Raju, 2020 ). The government lso absorbed the cost of water and electricity for poor households be- ween March and May 2020 ( Dadzie & Raju, 2020 ). Furthermore, soft oans were given to small and medium-scale businesses through the Na- ional Board for Small-Scale Industries ( World Bank, 2020 ). This initia- ive was part of the Coronavirus Alleviation Program-Business Support cheme (CAP-BuSS), which aimed to protect jobs, and livelihoods and ffer support to micro and SMEs. Indeed, the total amount invested in he program was GHC 600 million ( Adams, 2020 ). Additionally, the gov- rnment also drew support from existing programs such as the Ghana roductive Safety Net Project, which is a collaborative program be- ween the government of Ghana and international development part- ers to support households and businesses recover from the pandemic World Bank, 2020 ). The government also used existing pro-poor pro- rams to offer support to vulnerable households. For instance, the gov- rnment provided an additional one-off round of cash transfers to liveli- ood empowerment against poverty (LEAP) beneficiaries, with an ad- itional top-up benefit of GHC20 to urban beneficiaries and GHC 50 to ural beneficiaries ( Dadzie & Raju, 2020 ). It is worthy of note that the OVID-19-related support programs, like other existing programs such s LEAP, are not intended to directly eradicate poverty or negative liveli- ood impacts, either in their policy framing or amount or frequency of upport ( Ministry of Finance, 2020 ), and as a matter of fact, explains he several philanthropic interventions by civil society organizations to omplement state support. Indeed, there was also philanthropic support from individuals, reli- ious bodies, politicians, and the private sector. Philanthropic support as in two forms. The first was direct support to citizens, mostly in the orm of food and cash donations. For instance, many FBOs donated food tems to their congregants as well as vulnerable persons living in the ommunities in which they operated ( Prempeh, 2021 ; WACSI, 2020 ). he second form of philanthropic support was those made to the COVID- 9 National Trust Fund (CNTF) to assist in the fight against COVID-19. S. Okyere, L. Frimpong, M. Abunyewah et al. Urban Governance 3 (2023) 228–242 Fig. 5. The study area in national and regional context (Authors’ Construct, 2022). T c l u g 3 5 c 4 y C i A p o t o b t v u s i o a a F T d i ( p 1 ( i t 3 t 7 t m i i b T u t o r i 5 n c t d he CNTF was a government vehicle established through an act of par- iament to leverage other resources to fight the pandemic. Many or- anizations and individuals made cash donations to CNTF. As of June 0, 2020, CNTF had mobilized GHC 53,911,249.87 from individuals, hurches, and corporate bodies ( Ministry of Finance, 2022 ). . Overview of the study area: Adenta municipality The Adenta municipality is located in the Greater Accra Metropolitan rea (GAMA) ( Fig. 5 ), where Ghana recorded its first COVID-19 cases n March 12, 2020. Since then, GAMA has become a pivot of discussions n the nexus between health and urban socio-economic dynamics and hus provides a fertile ground to explore the pandemic implications on rban livelihoods. Within GAMA, Adenta municipality, the geograph- cal setting for this study, has a poverty incidence below 20%, with n estimated number of poor people of less than 10,000 ( GSS, 2015 ). urther, over the years and as a result of in-migration, there is evi- ence of a pocket of low-income squatters living in the municipality Alba & Bruns, 2022 ). It has a population size of about 237,546 with 17,841 males and 119,705 females. The total number of households n the municipality is about 73,281 and the average household size is .2 ( GSS, 2021 ). The informal sector of the municipality employs about 0% of the labour force, with the remaining 30% employed by the for- al sector (GSS, 2014). The municipality has, in recent times, witnessed ncreased physical development and the growth of the informal sector. he majority of these informal sector workers are migrants who come o learn a trade or seek greener pastures in Accra. The municipality’s esponse to the pandemic was heavily reliant on national government nterventions (e.g., absorbing utility bills, free delivery of food and daily ecessities to poor households, soft loans to small-scale businesses) and ivil society COVID-19 relief support. The 2021 Annual Action Plan of he Municipality’s Medium-Term Development Plan provides no con-233 rete actions for the prevention and mitigation of COVID-19 impacts on rban livelihoods ( Adentan Municipal Assembly, 2018 ). . Research methodology This paper deploys Structural Equation Modelling (SEM) to anal- se the moderating role of COVID-19-related support on the effects of OVID-19 impacts on urban livelihood capitals in the Adenta Munic- pality of the Greater Accra Region in Ghana. Hair et al (2021) ex- lains moderation as describing a situation where the relationship be- ween two constructs is not constant but it is also influenced or shaped y a third variable. This third variable is often termed the moderator ariable or construct ( Sauer & Dick, 1993 ; Hair et al., 2021 ). Indeed, tudies on COVID-19 pandemic reveal that its impact on residents is ften influenced by support interventions from different actors such s governments, families, friends, NGOs, etc. ( OECD, 2021 ; Visagie & urok, 2021 ; Akrofi & Antwi, 2020 ; Osuteye et al., 2020 ). Most of these nterventions were aimed at cushioning residents and businesses to im- rove their conditions rather than directly addressing negative impacts Ministry of Finance, 2020 ). This shows that the relationship comprises wo constructs and a moderating construct or variable. In this study, he two constructs are COVID-19 impacts and urban livelihoods capi- als while the moderator variable is COVID-19-related support. Hence n this moderation analysis, the strength or direction of the relationships etween COVID-19 impacts and urban livelihoods capitals are examined sing COVID-19-related support. This aligns with Hair et al. (2021) rec- mmendation for the appropriate use of moderation analysis. .1. Survey design and data collection To achieve the research aim, the team employed a cross-sectional esign. This design was selected because of its ability to link data, hy- S. Okyere, L. Frimpong, M. Abunyewah et al. Urban Governance 3 (2023) 228–242 p t w s i c b r t g w b t t d d s v m E h m a t s a K m w i w s p b h i t C a t t v a s a 6 n a 6 h v c m r a f t d A e t 1 r t o t e i t c a E t e 6 d S c c c r o P v K w fi T H T t C d 5 p g p 𝜆 s b l n w 1 r a r 5 i c a s t v f 2 w m othesis, model development and generalized results ( Barratt & Kir- an, 2009 ). A structured questionnaire survey was designed through n-depth literature and administered by 10 graduate research assistants etween November 2021 and January 2022. In terms of the data collec- ion, the municipality’s estimated total number of households of 73,281 as considered as the sample frame. Using the sample size determina- ion table published by Yamane (1967) and Israel (2003) , at a confi- ence level of 95%, P = .5 and a level of precision of ± 5%, an estimated ample size of 400 was deemed appropriate for the total households. The ultistage sampling technique was adopted to ensure that each house- old head had an equal chance of taking part in the survey. To ensure representative sample, the stratified sampling technique was used to ample 100 respondents from each of the four (4) zonal councils namely oose, Gbentanaa, Nii Ashale and Sutsurunaa. The data collection tool as a questionnaire designed using the Kobo Collect App. Respondents ere given a paper copy of the questionnaire for their perusal before articipating in the questionnaire survey. In each of the zonal councils, ousehold heads or in their absence a representative was selected for he survey. The purpose of the study was explained to the respondents nd the survey commenced only with their full consent. The survey questionnaire was made up of 3 parts. The first part pro- ided an introductory letter that highlighted the brief profile of the re- earch team including institutional affiliations, the research purpose, nd the voluntariness of participants. The second part of the question- aire gathered information on respondents’ socio-demographic char- cteristics such as gender, age, level of education, marital status, and ousehold size. Section 3 of the questionnaire contained items (manifest ariables) measuring the 6 latent constructs (Covid-19 impact, financial apital, social capital, human capital, physical capital, and COVID-19 elated support) used in the study as displayed in Table 1 . Each mani- est variable was measured using a Likert scale ranging from 1 (strongly isagree) to 5 (strongly agree). According to Taherdoost (2016) , the main purpose of using a ques- ionnaire is to gather relevant data reliably and validly. In ensuring the eliability and validity of the data collected, a 2-stage approach rec- mmended by Abunyewah et al. (2020) and Fatemi et al (2020) was mployed. Firstly, the questionnaire — underpinned by in-depth litera- ure and existing theories —was given to two academic teams (Australia nd Ghana) for assessment and review. Suggestions from the academic eam were considered and submitted to a team of industry experts for valuation and additional feedback. The feedback from the team of aca- emics and industry experts enhanced the questionnaire’s readability. econdly, the updated questionnaire was piloted across the four zonal ouncils of the municipality with 24 participants (6 in each zonal coun- il). The pilot data was analyzed to measure the reliability and validity f the questionnaire. Results from the pilot study showed that the sur- ey instrument was reliable ( 𝜶 ≥ 0.7) and valid (AVE ≥ 0.5), as it aligns ith recommended reliability and validity values ( Ursachi et al., 2015 ). his was followed by a survey of 400 participants in the study area. In general, all the demographic characteristics aligned with the pat- erns in the municipality except for average household size. During the ata collection, data collectors observed household heads’ inclusion of ersons temporary staying with them due to the COVID-19 pandemic as art of their households. This might be the reason the average household ize of the sample is higher than the municipality’s average. Neverthe- ess, other socio-demographic data reported in this study (see Table 2 ) hich conforms to recent census figures ( GSS, 2021 ) demonstrate the eliability and robustness of the survey data. .2. Data analysis Data from the study were analyzed with the aid of two statistical oftware’s: SPSS version 28 and AMOS version 28. The SPSS was used o calculate descriptive statistics such as mean, standard deviation and requency including Exploratory Factor Analysis (EFA) while the AMOS as used to estimate the Confirmatory Factor Analysis (CFA) and struc-234 ural model. Baumgartner and Homburg (1996) point out that most re- earchers employing SEM as an analytical tool often proceed to estimate orrelation analysis, EFA, CFA and SEM without paying attention to the aw data. According to them, when this occurs the correlation matrix enerates a multitude of factors that may call into doubt the applica- ility of the statistical procedure. Learning from these occurrences, the eam thoroughly checked the questionnaire surveys for errors before, uring and after coding. Preliminary data analyses to check for missing ariables, outliers, multicollinearity and normality were run as well. An FA, a CFA and SEM were estimated to evaluate the study’s proposed odel. To test the proposed model, an EFA was computed to uncover he common factors that are accurately associated with the latent vari- bles. The results from the EFA served as input to run the CFA. The easurement model was assessed and validated using construct valid- ty (standardized factor loadings, average variance extracted, and con- truct reliability). In addition, the model was also assessed using a com- ination of absolute fit indices (GFI, AGFI and Chi-square), relative fit ndices (IFI, TLI and NFI) and non-centrality-based indices (RMSEA and FI). As a sequel to the measurement model’s validation, the research eam estimated the structural model to assess the relationships between he latent constructs and associated manifest variables, path coefficients nd model fits using the GOF indices. . Results .1. Socio-demographic characteristics of respondents Data collected from the study respondents shows that 57.2% are ales while 42.8% are females. Most respondents (51.7%) are married, nd the average household size is approximately 5. In terms of educa- ion, 98.2% have some form of formal education ( see details in Table 2 ). ll demographic characteristics conformed to the municipality trends xcept for average household size, possibly hinting at how the COVID- 9 pandemic seemingly altered the living arrangements of households in he municipality. Indeed, some studies on the COVID-19 pandemic show hat it altered the living arrangement of many households, often bring- ng families together —albeit amidst increased stress and interpersonal onflicts — thereby increasing household sizes during the pandemic (see vandrou et al. 2021 ). .2. Exploratory factor analysis To identify the manifest variables that adequately define the latent onstructs adopted in the study, the research team estimated an EFA. In unning the EFA, we employed the Principal Component Analysis and romax as the extraction and rotation methods respectively going by aiser’s eigenvalue of greater than 1 criterion, 6 factors were identi- ed as depicted in Table 3 . In addition to this criterion, we adopted the oward (2016) approach which excludes factors that load below 0.4. hese results also align with the number of variables identified a priori. omponent 1, 2 and 3 (retained 5 items each) and component 4 and (retained 4 items each), component 6 (retained 3) had eigenvalues reater than 1 respectively ( 𝜆= 5.69; 𝜆= 4.46; 𝜆= 3.87; 𝜆= 3.21; 𝜆 = 1.93, = 1.23). Specifically, item 4 for social capital (Social interactions were roken down as a result of Covid-19), item 1 for human capital (I have ot been able to acquire and utilize my knowledge as a result of Covid- 9), item 1 for physical capital (As a result of Covid-19, my household ssets depreciated in value) and item 6 for COVID-19 related support (I eceived support from local government representatives/politicians dur- ng Covid-19) were deleted. These items were excluded from further dis- ussion because their factor loadings were less than 0.4 ( Howard, 2016 ) nd eigenvalues were less than 1. Overall, the 6 components identified explained 78.36% of the total ariance which meets the recommended threshold of 60% ( Hair et al., 012 ). Using Harman’s One-Factor test showed an absence of common ethod bias since the first extracted factor did not account for more than S. Okyere, L. Frimpong, M. Abunyewah et al. Urban Governance 3 (2023) 228–242 Table 1 Constructs for the study. Latent Construct Item Source Code Covid-19 Impact My accessibility to food was impacted by Covid-19 Asante & Mills (2020) CI1 My accessibility to clean water was impacted by Covid-19 Ojogiwa & Akinola (2020) CI2 Covid-19 widened the inequality in accessing all forms of basic needs Bukuluki et al. (2020) CI3 As a result of Covid-19, I have sold some of my household assets Aragie et al. (2021) CI4 As a result of Covid-19, my standard of living significantly fell Schotte & Zizzamia (2021) CI5 Financial Capital Covid-19 has reduced my ability to save money Carney et al. (1999) FC1 Covid-19 has impacted my creditworthiness from banks/friends DFID (1999) FC2 Covid-19 has reduced remittances received from family and friends Asegie et al. (2021) FC3 Covid-19 has reduced the amount of money or monetary assistance I can give to Gallup & Sachs, (2001) FC4 family/friends Gustafsson-Wright et al. (2011) Covid-19 has reduced the amount of money I spend on other personal things I need Masanjala (2007) FC5 Social Capital Covid-19 disorganized community meetings and gatherings Carney et al. (1999) SC1 Covid-19 affected opportunities for social networking and bonding DFID (1999) SC2 Covid-19 affected travel schedules and plans Morsut et al. (2021) SC3 Social interactions were broken down as a result of Covid-19 Makridis & Wu (2021) SC4 Alonge et al. (2019) Wong & Kohler (2020) Yu et al. (2021) Masanjala (2007) Hunter et al. (2011) Bhandari & Alonge (2020) Human Capital I have not been able to acquire and utilize my knowledge as a result of Covid-19 Carney et al. (1999) HC1 I have not been able to utilize my skill sets because of Covid-19 DFID (1999) HC2 My health condition was impacted by Covid-19 Callegari & Feder, (2021) HC3 I lost my job as a result of Covid-19 Zinyemba (2021) HC4 I have taken on an additional job as a result of Covid-19 Gustafsson-Wright et al. (2011) HC5 Myers & Thomasson ( 2021 ) Okediya (2020) Masanjala (2007) Hunter et al. (2011) Bhandari & Alonge (2020) Physical Capital As a result of Covid-19, my household assets depreciated in value Carney et al. (1999) PC1 As a result of Covid-19, I changed my place of residence or abode DFID (1999) PC2 As a result of Covid-19, my children cannot go to school Ulya et al. (2021) PC3 As a result of Covid-19, my family cannot visit recreational sites Callegari & Feder (2021) PC4 As a result of Covid-19, members of my household that are sick cannot access Nsoesie et al. (2015) PC5 certain hospital services Maphanga & Henama (2019) Hunter et al. (2011) Bhandari & Alonge (2020) Masanjala (2007) Hunter et al. (2011) Bhandari & Alonge (2020) COVID-19 I received support from families during Covid-19 Visagie & Turok (2021) CS1 related support I received support from the central government during Covid-19 Akrofi & Antwi (2020) CS2 I received support from friends during Covid-19 Otsuteye et al. ( 2020 ) CS3 I received support from religious bodies during Covid-19 Dadzie & Raju (2020) CS4 I received support from NGOs during Covid-19 Adams (2020) CS5 I received support from local government representatives/politicians during World Bank ( 2020 ) CS6 Covid-19 Prempeh (2021) WACSI ( 2020 ) 5 Table 2 Socio-demographic characteristics of respondents. 2 m Socio-demographic factors Components Percentage (%) c Gender Male 57.2 r Female 42.8 s Household 1-5 20.3 t Size 6-10 77.5 + K 10 2.2 Age 18-26 17.8 0 27-35 ( 48.2 36-44 20.0 y 45-53 9.0 54-62 3.8 63 + 1.2 6 Marital Single 44.0 Status Married 51.7 Divorced 2.3 w Separated 2.0 Education No Formal Education 1.8 p Level T Primary/Middle/JHS 32.7 Senior High School 39.3 a Tertiary 26.3 c l 235 0% of the total variance ( Podsakoff & Organ, 1986 ; Podsakoff et al., 003 ). In addition, we used the determinant score of the correlation atrix approach recommended by Samuels (2017) to test for multi- ollinearity. The result showed a determinant score greater than the ecommended threshold of 0.00001 ( Field, 2013 ), suggesting an ab- ence of multicollinearity issues. The Kaiser-Meyer-Olkin and Bartlett’s ests were used to test the appropriateness of the factor analysis. The aiser-Meyer-Olkin sampling adequacy coefficient for the dataset was .81, whereas the Bartlett test of Sphericity was statistically significant 2 𝜒 = 6031.26, df = 325, p = 0.000). This indicates that the factor anal- sis is justified, and the data suits the analysis carried out. .3. Confirmatory factor analysis (CFA) A CFA was performed to assess the manifest variable relationship ith the latent constructs. Results shows an adequate fit ( 𝜒2/df = 1.45, = 0.000; GFI = 0.89; AGFI = 0.86; CFI = 0.98; IFI = 0.98; NFI = 0.94; LI = 0.98 and RMSEA = 0.04). The Cronbach’s Alpha was employed to ssess the reliability of the constructs. This helped to assess the internal onsistency of the scale items used in the study. As shown in Table 5 , the atent variables showed a Cronbach alpha that meets the recommended S. Okyere, L. Frimpong, M. Abunyewah et al. Urban Governance 3 (2023) 228–242 Table 3 Exploratory Factor Analysis. Items Financial Capital Covid-19 Impact COVID-19 Related Support Human Capital Physical Capital Social Capital FC1 .938 FC2 .967 FC3 .962 FC4 .938 FC5 .960 CI2 .936 CI3 .947 CI4 .931 CI5 .838 CS1 .933 CS2 .956 CS3 .855 CS4 .873 CS5 .888 HC2 .900 HC3 .910 HC4 .921 HC5 .880 PC2 .814 PC3 .751 PC4 .726 PC5 .818 SC1 .786 SC2 .758 SC3 .673 Table 4 w Correlation matrix and the square root of AVE. i Components 1 2 3 a 4 5 6 F Financial Capital 0.94 ( Covid-19 Impact 0.07 0.89 COVID-19 Related Support 0.11 0.02 0.88 L Human Capital -0.09 -0.01 -0.08 0.87 t Physical Capital 0.08 -0.09 0.29 -0.17 0.72 Social Capital 0.19 -0.20 -0.40 -0.13 0.29 0.72 C Diagonal values in bold are the AVE of t each construct t c t t H c u i a p i ( w S c s i 7 v 6 a w t w p i e r u p c T b e t 1 6 2 C i A t f c 1 r i f hreshold of equal to or greater than 0.7 (FC = 0.97, CI = 0.95, CS = 0.94, C = 0.93, PC = 0.77, SC = 0.77). A convergent validity test was conducted sing the criteria suggested by Hair et al. (2006) . The CFA showed statistically significant factor loading, between 0.65-0.98, compos- te reliability was ranging from 0.77-0.97, and all the constructs’ AVE as greater than 0.5 as depicted in Table 5 . Based on Fornell and Lar- ker (1981) approach of assessing the discriminant validity, our results howed that the square root of the constructs’ AVE was greater than the nter-correlation with other constructs in the model (shown as diagonal alues in Table 4 ). .4. Structural equation model (SEM) Following acceptable reliability and validity tests, a structural model as estimated to test the hypotheses of the study. This is examined us- ng the standardized factor estimates and the significance level. Overall, esults from the SEM analysis showed an adequate fit ( 𝜒2/df = 1.54, = 0.000, GFI = 0.91; AGFI = 0.89; CFI = 0.98; IFI = 0.98; NFI = 0.94; LI = 0.98 and RMSEA = 0.05). Fig. 6 shows the statistically significant stimates of the latent constructs and the hypotheses tested. .5. Moderation effects of COVID-19 related support In this study, we used the step-by-step approach recommended by ikens and West (1991) and Dawson (2014) to test the moderation ef- ects of COVID-19 related support on the relationship between COVID- 9 impact and livelihood capitals. This approach was selected because t centers data and mitigate the collinearity of the main effect variables236 ith the interaction terms ( Aikens and West, 1991 ). Using this approach nvolves three stages. In the first place, data for the independent vari- ble, moderator, and dependent variables were standardized (z-scores). ollowing this, we multiplied the z-scores of the independent variable COVID-19 impact) with the moderator (COVID-19 related support). astly, the model was run and the resultant output was plotted on a wo-way interaction excel sheet, as depicted in Fig. 7 . The results showed a statistically significant correlation between OVID-19 impact ( 𝛽= -0.04, p = 0.000) and financial capital. Also, here was a statistically significant relationship between the interac- ion terms [ 𝛽 (COVID-19 impact) = 0.02, p = 0.000] and financial apital. However, there was no statistically significant relationship be- ween COVID-19 impact and social capital, physical capital and human apital ( Table 6 ). This means that the relationship between COVID-19 mpact, and financial capital is moderated by COVID-19-related sup- ort. The GOF and other parameters also proved that the model is good 𝜒2/df = 5.43, GFI = 1.00, NFI = 1.00, IFI = 1.00, CFI = 1.00, RM- EA = 0.06). . Discussion The COVID-19 pandemic has had significant impacts on humanity nd continues to be a growing threat to people’s livelihoods. To deal ith this threat, it is imminent to have knowledge and information on he level and extent of COVID-19 impacts on livelihood to design ap- ropriate interventions. Using Ghana as a case study, this study hypoth- sized that the COVID-19 pandemic has a negative relationship with rban livelihood capitals namely: financial, human, social, and physical apitals. The results show statistically significant negative relationships etween COVID-19 impacts and the livelihood capitals. This confirms he observation from the literature that health pandemics like COVID- 9 often have negative impacts on residents’ livelihoods ( Braam et al., 021 ; Rahman et al., 2021 ). Specifically, the study reveals that the OVID-19 pandemic reduced residents’ household expenditure and abil- ty to save money, lowered their creditworthiness, reduced the remit- ances they received from and give to family and friends. This finding onfirms other studies that found that malaria and HIV/AIDS pandemics educe income capacity, deplete savings, and worsen credit availability or households ( Gallup & Sachs, 2001 ; Gustafsson-Wright et al., 2011 ). S. Okyere, L. Frimpong, M. Abunyewah et al. Urban Governance 3 (2023) 228–242 Fig. 6. Structural Model. Fig. 7. Moderation effect of COVID-19-related support. W C 1 t d c t ( o c r r d s t A b l a T n i a 1 f r d h t s ( i 2 p p a a s fi e i f t r r h g ( ith the social impact of COVID-19, our study revealed that the COVID- 9 pandemic reduced social interactions and networking among resi- ents and even truncated budding relationships necessary for building heir social capital. Moreover, some residents also changed their place f residence with many unable to send their children to school or visit ecreation sites and access certain hospital services. Collectively, these emonstrate how the COVID-19 pandemic has engendered an exten- ive disruption to residents’ everyday activities ( Haleem et al., 2020 ; pplebaum et al., 2021 ) and in other cases destructed urban residents’ ivelihoods, thereby leading to severe hardships ( Adam et al., 2020 ). hese livelihood disruptions and destructions make efforts toward build- ng community sustainability and resilience challenging as the COVID- 9 pandemic has seemingly truncated many signs of progress made by esidents and government actions to reduce poverty and improve liveli- ood outcomes ( Bukari et al., 2021 ; Diop & Asongu, 2021 ). Additionally, the need for a structural response to health pandemics Fakhruddin et al., 2020 ; Daszak et al., 2021 ; Schmidt-Sane et al., 021 ) is supported by this study’s findings. Despite, the COVID-19 andemic triggering support initiatives to help residents cope with and dapt to this health disaster ( Wilkinson et al., 2020 ; OECD, 2021 ), the ndings show how COVID-19-related support did not minimize the mpact of the pandemic on all livelihood capitals. Aside from reducing he impacts of the pandemic on residents’ financial capital, this paper eveals how support from families and friends, FBOs, NGOs and local overnment representatives/politicians were unable to weaken the237 OVID-19 pandemic impacts on social, human, and physical capitals, hereby unable to improve overall urban residents’ livelihood out- omes. Indeed, this finding underscores the call by Wilkinson et al. 2020) to be mindful of the pandemic response strategies, as some an be ineffective and further undermine the livelihood capabilities of esidents. Some reasons can be attributed to these. Firstly, the pervasiveness of he COVID-19 pandemic means that family and friends who might have een in a position to help during disaster events were also impacted nd thus were not capable of providing adequate support to more vul- erable residents. For instance, residents confirmed reductions in the mount of money or monetary assistance they can give to family and riends. As observed by Bisong et al. (2020) , declines in remittances to eveloping countries are undermining efforts to tackle the impacts of he COVID-19 pandemic and disrupting countries’ efforts in building ustainable communities. Hence, findings from this study suggest that nterventions improving residents’ financial capital can have more im- act in reducing the negative impacts of COVID-19 on residents. This ligns with findings from Coulaud et al. (2023) , who observed financial upport can weaken the adverse impacts of the COVID-19 pandemic, but mphasized that financial support only contributes to a broader set of actors that can help reduce the pandemic’s impacts. Again, significant eductions in the funding of NGOs and governments to support their umanitarian and socio-economic development projects and programs Lone & Ahmad, 2020 ; Wilke et al., 2020 ; Asogwa et al., 2022 ) resulted S. Okyere, L. Frimpong, M. Abunyewah et al. Urban Governance 3 (2023) 228–242 Table 5 CFA factor loadings, reliability and validity of constructs. Items Financial Capital Covid-19 Impact COVID-19 related support Human Capital Physical Capital Social Capital FC1 0.90 FC2 0.97 FC3 0.98 FC4 0.91 FC5 0.95 CI1 0.89 CI2 0.92 CI3 0.78 CI4 0.93 CI5 0.92 CS1 0.92 CS2 0.96 CS3 0.71 CS4 0.87 CS5 0.93 HC2 0.87 HC3 0.87 HC4 0.90 HC5 0.84 PC2 0.78 PC3 0.69 PC4 0.68 PC5 0.72 SC1 0.79 SC2 0.81 SC3 0.65 AVE 0.88 0.79 0.78 0.76 0.52 0.52 CR 0.98 0.95 0.95 0.93 0.81 0.76 IR 0.97 0.95 0.94 0.93 0.77 0.77 i t m a h t s c i t a w s F i F s C i s t f T n f m i f t d r n c s p j p S m s t f p t t i d fi m l s i p n n p o c a i s a t F t e l a h n reduced capacities to provide a broad range of interventions to help inimize and tackle the impacts of the pandemic on residents’ liveli- ood capitals. Here, Aberman et al. (2014) argues that while support uch as safety nets from governments, NGOs, FBOs, etc. can be helpful n assuaging the negative impacts of health pandemics, funding avail- bility often constrains their effective implementation and comprehen- iveness. Again, this re-echoes our findings that addressing the adverse mpacts of the COVID-19 pandemic on residents’ livelihoods requires a tructural and multipronged response. Secondly, a reason why COVID-19-related support seemed unrespon- ive to social, human, and physical capital outcomes can be attributed o government bans on residents’ movements to mitigate transmission. hese bans constrained accessibility and mobility to school, family and riends, recreation sites, and even certain hospital services rather than mproved them ( Brauner et al., 2021 ). Consequently, we find that during he COVID-19 outbreak in Ghana, government enforcement of lockdown estricted residents’ movements and banned activities such as weddings, hurch services, parties, and other entertainment events that brought eople together to socialize and network. These restrictions inhibited eoples’ face-to-face contact with their friends, families, and the com- unity and the support that results from these interactions. This is likely he reason why the COVID-19-related support was unresponsive to im- roving residents’ social capital, as residents noted in the affirmative hat COVID-19 disorganized community meetings and gatherings and isagreed that COVID-19 strengthened their social networks. Similar ndings were observed in China ( Yu et al., 2021 ), where COVID-19 ockdown restrictions limited movements, thus negatively affecting res- dents’ social capital. Wong and Kohler (2020 : (2), therefore, argue a eed to transcend a one-size-fits-all approach to “social capital-centric ublic health approach ” to health pandemics such as COVID-19 since so- ial distancing policies such as post-exposure quarantining and shelter- n-place orders significantly interrupts residents everyday social inter- ctions and limits their access to traditional channels of social support. urthermore, the pandemic induced spontaneous reactions from gov- rnments, NGOs, FBOs, etc. whose efforts were mostly uncoordinated nd often without recourse to community-based organizations and sys-238 ems that can help with the effectiveness of the interventions. Hence, lthough Alonge et al. (2019) and Frimpong et al. (2022) emphasize he immense roles of these actors in restoring and strengthening so- ial capital during health pandemics, the spontaneous and ad-hoc na- ure of many of these interventions limited community partnerships hich seem to have not supported social capital enhancement. Indeed, rimpong et al. (2022) observed this with COVID-19 interventions in reetown, Sierra Leone, and called for a structural response to how OVID-19-related support can be effectively implemented by using ex- sting community support systems and partnerships. Also, we find that the partial lockdown that resulted in about 90% of ormal and informal businesses reporting negative effects on their busi- esses ( GSS, 2020 ) can be attributed to the fact that many residents re- ained economically unproductive during the lockdown. With many in- ormal businesses, which employ the majority of urban residents, closed uring the pandemic ( GSS, 2020 ; Aduhene & Osei-Assibey, 2021 ), it is ot surprising that residents were unable to utilize their knowledge and killsets during the partial lockdowns —with some residents losing their obs and others unable to take up employment even if they wanted to. ince COVID-19-related support was in the form of utility subsidies, food upplies, and cash transfers ( Dadzie & Raju, 2020 ), this made it difficult or residents to use and augment their knowledge and skillset to enhance heir livelihoods. This could be the reason why H7 was not supported n the analysis. In relation to physical capital, COVID-19 restrictions limited move- ents and access to infrastructure services unless it was an emergency, uch as health care services in Ghana. Also, the academic calendar was ut on hold for ten months, starting in March 2020, and students could ot attend school ( World Bank, 2022 ). Attempts to encourage distance r online learning were also constrained by poor internet connectivity nd equipment and the general unpreparedness of Ghana’s education ystem to deploy remote learning (Aurino et al., 2021). Furthermore, he support received by residents was simply inadequate, causing some o sell part of their household assets to sustain themselves during the ockdown. For example, while food items were shared, not every house- old received them, and these were also not consistent throughout the S. Okyere, L. Frimpong, M. Abunyewah et al. Urban Governance 3 (2023) 228–242 Table 6 Summary of findings. Hypotheses Path Outcome H1 : Covid-19 pandemic impact has a negative relationship with Supported financial capital H2 : Covid-19 pandemic has a negative relationship with human Supported capital H3 : Covid-19 pandemic impact has a negative relationship with Supported social capital H4 : Covid-19 pandemic impact has a negative relationship with Supported physical capital H5 : COVID-19-related support weakens the negative relationship Supported between covid-19 pandemic impact and financial capital H6 : COVID-19-related support weakens the negative relationship Unsupported between covid-19 pandemic impact and social capital H7 : COVID-19-related support weakens the negative relationship Unsupported between covid-19 pandemic impact and human capital H8 : COVID-19-related support weakens the negative relationship Unsupported between covid-19 pandemic impact and physical capital 239 S. Okyere, L. Frimpong, M. Abunyewah et al. Urban Governance 3 (2023) 228–242 l t s F l i c c s D ( p u v C T s a y s c t o d F K S S s r F e i C I n g i c m p R a A 8 A i A t c A u n p A t i o e A e h A p t o A t A t a A e p A r h A t a d A p A a h p A t u A u 1 A d 1 ockdown period. Thus, we find that the nature of the COVID-19-related upport did not lead to the reopening of schools or opportunities for on- ine learning, opportunities to access healthcare, and/or increased ac- ess to food, thus resulting in H8 not being supported by the analysis. Indeed, while the implementation of COVID-19 restrictions is not urprising given the need to contain the spread of the COVID-19 virus Brauner et al., 2021 ), our study reveals how certain necessary health andemic interventions engender negative livelihood outcomes, partic- larly for low-income residents, for which complementary support inter- entions are needed to counter their negative effects ( Devereux, 2021 ). hese observations consolidate and justify the use of SEM in this tudy. It enabled this research to unravel the structural interconnections mong COVID-19, urban livelihoods capitals, and COVID-19-related upport, demonstrating that any response to addressing vulnerabili- ies and building resilience can be effective with structural health pan- emic responses . Akin to other studies ( Couland et al., 2023 ; Wong & ohler, 2020 ; Fakhruddin et al., 2020 ; Daszak et al., 2021 ; Schmidt- ane et al., 2021 ), this study confirms that structural health pandemic esponses reveal that no individual COVID-19-related supports can mod- rate all livelihood outcomes. This demonstrates the limits to some OVID-19-related support in providing sustainable livelihood outcomes ecessitating an intentional move towards developing and implement- ng holistic, multipronged, and integrated approaches that speak to the ulti-dimensionality of urban livelihoods as this is an effective way of roviding sustained and long-term relief from the COVID-19 pandemic nd future health pandemics. . Conclusions The onslaught of the COVID-19 pandemic unraveled the vulnerabil- ties of urban livelihoods —financial, human, social, and physical capi- als. For already vulnerable urban areas, many of which are global south ities characterized by poverty, unemployment, inadequate access to ed- cation and health services, poor sanitation infrastructure, and gover- ance systems, the onslaught indicates an aggravation of the already recarious impoverishment of urban residents. As this study has illus- rated through the study of COVID-19 impacts on urban livelihoods cap- tals in suburban Accra, residents were impacted negatively at all levels f their livelihoods —with the pandemic disrupting their everyday socio- conomic endeavors. Like development actors across the globe, the Gov- rnment of Ghana, NGOs, FBOs, and families and friends stepped in to elp residents impacted by the pandemic. Such COVID-19-related sup- ort, however, had limited impacts on urban livelihoods capitals. From his research, the support was only able to minimize the negative impact f the COVID-19 pandemic on financial capital and not the other capi- als. This necessitates a move towards a holistic and integrated response o the negative impacts of the COVID-19 pandemic and future health dis- sters on residents’ livelihoods capitals. Using SEM provided a means to stablish the structural interrelations among COVID-19 impacts, sup- ort received by urban residents, and the degree to which the support eceived by residents affected the pandemic’s impacts on urban liveli- oods capitals. While this study affirms many previous studies of how he health pandemic negatively impacts livelihoods, it also advances the rgument that the resulting support that emanates from such health pan- emics can minimize negative impacts when approached from a com- rehensive perspective. For this reason, governments, NGOs, and FBOs t the forefront of initiating support interventions for those impacted by ealth disasters such as the COVID-19 pandemic need to provide com- rehensive support interventions and coordinate their activities so that heir efforts are complementary. A limitation of this study is that beyond establishing the structural nderpinnings of COVID-19 impacts and COVID-19-related support on rban livelihoods capitals, it does not account for differences in COVID- 9 impact across different socio-economic groups and communities. It oes not also detail the moderating roles of the specific kinds of COVID- 9-related support on urban livelihood capitals. These are vital for fu-240 ure research to help inform governments, NGOs, family and friends and BOs to understand which support initiatives would be more effective n minimizing the negative impacts of COVID-19 on urban livelihoods apitals. eclaration of Competing Interest The authors declare that they have no conflict of interest. RediT authorship contribution statement Seth Asare Okyere: Conceptualization, Data curation, Formal anal- sis, Supervision, Writing – original draft. Louis Kusi Frimpong: Con- eptualization, Data curation, Formal analysis, Investigation, Methodol- gy, Writing – original draft. Matthew Abunyewah: Conceptualization, ormal analysis, Methodology, Supervision, Writing – original draft. tephen Kofi Diko: Conceptualization, Data curation, Formal analy- is, Methodology, Supervision, Writing – original draft. Md. Nawrose atemi: Conceptualization, Data curation, Supervision, Writing – orig- nal draft. 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