Original Article/Research Costs and psychosocial burden of tuberculosis to the treatment supporters in Ghana Robert Bagngmen Bio a,* , Patricia Akweongo b, John Azaare c, Francis Adane b, Kasim Abdulai d, Richard Ali Laar a, Abraham Titiati a a College of Health and Well-Being, Kintampo, Ghana b School of Public Health, University of Ghana, Legon, Accra, Ghana c School of Public Health, University for Development Studies, Tamale, Ghana d Department of Clinical Nutrition and Dietetics University of Cape Coast, Cape Coast, Ghana A R T I C L E I N F O Keywords: Ghana Bono region Direct cost Indirect cost Psychosocial burden Treatment Supporter Tuberculosis A B S T R A C T Objectives: Tuberculosis treatment supporters contribute crucially to tuberculosis control and prevention without financial compensation. The World Health Organization recommends direct observation of treatment, involving supporters who incurred costs for frequent health facility visits and waiting times, potentially impacting their socio-economic status. This study aims to inform tuberculosis control and prevention policy by determining the costs and psychosocial burden associated with treatment support. Methods: A cross-sectional cost-of-illness approach, data from 385 supporters were collected through validated questionnaires. Both direct and indirect costs were assessed, with psychosocial burden measured using the Zarit Burden Interview (ZBI) 12-item questionnaire. Results: Results reveal that, on average, supporters spent GHS 122.4 (US$21.1) monthly, constituting 19 % of their income. A significant 77.1 % experienced a high burden on the ZBI scale, with females facing a greater burden than males. Socio-demographic factors such as education, household size, income, and district of resi dence influenced both direct and indirect costs. Conclusion: In conclusion, the study underscores the substantial costs and psychosocial burden on tuberculosis treatment supporters and recommends extending the livelihood empowerment against poverty program in Ghana to cover treatment support costs. Introduction Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis, primarily affecting the lungs but capable of spreading to other organs [1]. It spreads through airborne droplets when an infected person coughs or sneezes. Prevention measures include the Bacillus Calmette-Guérin (BCG) vaccine, early screening, and infection control strategies like proper ventilation and respiratory hygiene [2]. Treatment involves a six-month antibiotic regimen, including rifampicin, isoniazid, pyrazinamide, and ethambutol, under the Directly Observed Treatment, Short-course (DOTS) strategy [2–4]. Different treatment supporters provide patients with informal care. They assist patients in adhering to treatment regimens, provide emotional and physical support, and may help with daily activities depending on the patient’s needs. Treatment supporters, may include family, friends, or community members offering support specific to treatment adherence [5]. Tuberculosis remains a significant public health challenge, especially in developing nations like those in Africa and Asia [6,7]. In Ghana, TB is widespread across all regions and districts, with alarming incidence and mortality rates reported in 2020 [8]. The Ministry of Health, in collab oration with the Ghana Health Service, has implemented strategies such as the Directly Observed Therapy Short Course (DOTS) to address these challenges [9]. In 2020, Ghana reported a TB incidence rate of 143 and a mortality rate of 49 per 100,000 populations [8]. This resulted in a concerning one-third of estimated TB cases leading to death, with only one-third of cases reported to health centers [8]. The DOTS strategy, a vital component of Ghana’s TB control efforts, involves treatment supporters who observe daily medication intake, ensure treatment completion, and provide social and psychological support [10–13]. * Corresponding author at: College of Health and Well-being, Kintampo, Ghana. E-mail address: bagngmen@gmail.com (R.B. Bio). Contents lists available at ScienceDirect Health Policy and Technology journal homepage: www.elsevier.com/locate/hlpt https://doi.org/10.1016/j.hlpt.2025.101060 Health Policy and Technology 14 (2025) 101060 Available online 20 June 2025 2211-8837/© 2025 Fellowship of Postgraduate Medicine. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. https://orcid.org/0000-0001-8552-5188 https://orcid.org/0000-0001-8552-5188 mailto:bagngmen@gmail.com www.sciencedirect.com/science/journal/22118837 https://www.elsevier.com/locate/hlpt https://doi.org/10.1016/j.hlpt.2025.101060 https://doi.org/10.1016/j.hlpt.2025.101060 http://crossmark.crossref.org/dialog/?doi=10.1016/j.hlpt.2025.101060&domain=pdf Despite the global success of DOTS, challenges persist, with varia tions in treatment success rates across regions and income levels [4,10, 12,14]. Many low-income countries in Africa and Asia struggle to meet the 85 % treatment success rate target set by the DOTS strategy [15–17]. A systematic review highlighted challenges, including direct and indi rect costs for TB patients and treatment supporters [18]. In low-income countries, repeated health facility visits contribute to costs and psy chological stress for supporters [4,10,19]. In Ghana, treatment supporters play a crucial role, yet there are no financial incentives to alleviate the costs they incur. This study aims to estimate the direct, indirect, and intangible costs of the DOTS strategy on treatment supporters. The Bono Region is used as a case study to understanding the costs implications for effective policy on tuberculosis control and prevention Figs. 1 and 2. Methods Our study employs a cost description, which is a form of partial economic evaluation to investigate the economic burden on adult TB treatment supporters, aged 18 and above. . This approach involves systematically identifying, measuring, and valuing the resources asso ciated with the intervention without comparing them to outcomes or alternative interventions [20]. Cost description is a type of partial eco nomic evaluation of health care programmes that aims at calculating the cost of a given disease or health care service [20]. The cost description was conducted from the societal perspective, as recommended by Drummond et al. [20], to reflect the economic burden of tuberculosis on the Ghanaian society. Data was collected through structured interviews employing close- ended questionnaires. Direct costs encompassed out-of-pocket ex penses for transportation, accommodation, feeding, and communica tion. The study employed the Zarit Burden Interview 12-item scale [21] to gauge the psychosocial burden. The Zarit Burden Interview (ZBI) 12-Item Scale is a widely used tool designed to assess the level of psychosocial burden experienced by caregivers of individuals with chronic illnesses, disabilities, or aging- related conditions. It measures the psychological, emotional, and physical stress caregivers face when providing care. It consists of 12 questions, each scored on a 5-point Likert scale (never, rarely, some times, quite frequently, nearly always). Indirect costs were estimated using the human capital approach [22], valuing productive time lost during Directly Observed Therapy Short Course (DOTS) center visits. Time spent on drug rations, waiting at the DOTS center, and supporting the TB patient in treatment were quantified in hours and converted to days based on an assumed 8-hour workday. For employed treatment supporters, the 2019 daily minimum wage rate (GHS 10.65 = US$ 1.99) was applied. Informal sector costs used the November 2019 average daily agricultural labor wage rate (GHS 37.5 = US$ 7.03) in the Bono Region. Costs were reported in Ghana Cedis (GHS) and converted to US dollars(2019 values) at an average exchange rate of GHS 5.33 for US$ 1, as per the Bank of Ghana interbank exchange rate, November 2019 (Available from:https://www. bog.gov.gh/economic-data/exchange-rate/), to ensure international comparison with other cost-of-illness studies. Study setting The study, conducted in six (6) districts in the Bono Region, cate gorized them as relatively urban (Berekum, Dormaa, Sunyani) and rural (Jaman North, Jaman South, Tain). These districts, sharing economic and demographic similarities, were chosen due to their high number of active tuberculosis cases. Inclusion and exclusion criteria Participants were eligible for inclusion if they were TB treatment supporters aged 18 years or older and had provided treatment support to TB patients for at least two months. Duration of support and clinical were key considerations for inclusion. Individuals were excluded if they had provided TB treatment support for at least two months but were clinically ill or if they had served as TB treatment supporters for less than two months. Sampling procedure For our study, we purposefully selected six hospitals in the Bono Region that had the highest number of TB cases. These districts are likely experiencing high burden of TB which is of public health concern. We identified treatment supporters from TB registers at each hospital and contacted them via phone before their scheduled drug ration date. During a visit to pick up their TB drugs at the hospital, we asked for their informed consent. Respondents who agreed to participate in the study were interviewed till we obtained the necessary sample of 385 re spondents. To minimize disruption to their routine care, questionnaires were administered after respondents had completed their treatment schedule and were preparing to leave the hospital. Data collection A validated questionnaire on estimating tuberculosis costs adapted from tool to estimate patients’ costs - tuberculosis coalition for technical assistance [23], was administered on 385 treatment supporters to collect information on the direct and indirect costs incurred. Using the below formula, we allocated the sample sizes proportional to the TB cases in each district as represented in Table 1. number of treatment supporters in each district total number of treatment supporters in the six districts × 385 Description of costs variables Table 2 present detailed description of the cost’s variables. Scoring of the Zarit Burden scale A 12-item survey using a 5-point scale (0 to 4) measured treatment supporter burden. Scores were summed for each item, resulting in a total score (0 to 48), with higher scores indicating greater burden. Based on Table 1 Number of tuberculosis patients on treatment as of 2018 and sample size allocated. No District No. of TB Cases Sample Size % 1 Berekum Municipality 112 112 631 X385 = 68 18 2 Dormaa Municipality 89 89 631 X385 = 54 14 3 Jaman North 78 78 631 X385 = 48 12 4 Jaman South 62 62 631 X385 = 38 10 5 Sunyani Municipality 170 170 631 X385 = 104 27 6 Tain 120 120 631 X385 = 73 19 ​ TOTAL 631 385 100 R.B. Bio et al. Health Policy and Technology 14 (2025) 101060 2 https://www.bog.gov.gh/economic-data/exchange-rate/ https://www.bog.gov.gh/economic-data/exchange-rate/ Ankri et al.’s suggestion, burden levels were classified: 0 to <10 (no to mild), 10–20 (mild to moderate), and >20 (high) [24]. Data analysis Descriptive statistic, cost estimation, scoring of Zarit Burden in terviews was the analysis techniques used. Socio-demographic pre dictors of the various cost’s components were performed using the one- way ANOVA test of equality of mean difference. A two-side P-val ue<0.05 was considered statistically significant. We conducted our an alyses using STATA version 14.0 (StataCorp, 2015, College Station, Texas, USA) and Microsoft Excel. Results The study involved 385 respondents (Table 3), primarily treatment supporters with a mean age of 39. Of these supporters, 53 % were male, 47 % were female, and 74 % were married. Additionally, 77.4 % were employed in the informal sector, while 22.6 % worked in the formal sector. In terms of income, 38 % earned between GHS500-GHS750, and 35 % earned less than GHS500. Family members constituted 72 % of the treatment supporters, 20 % were friends and occupation-wise, 56 % were farmers, 17 % were involved in trading, and 6 % worked as gov ernment employees. These socio-demographic characteristics provide insights into the diverse profile of the study participants. Direct and indirect costs of tuberculosis treatment support Table 4 reveals tuberculosis treatment support costs, totaling GHS35,837 (US$6724) per month. Indirect costs constitute 67 % (GHS23,853.16 or US$4475.26), while direct costs make up 33 % (GHS11,984.00 or US$2248.41). Monthly average cost per treatment supporter is GHS112.4 (US$21.1), with transportation (17 %) and feeding (15 %) as major direct cost components. Table 2 Description of Costs. Cost Type Cost Categories Description Direct Cost Feeding Direct out-of-pocket payments for foods and water Travel/transportation Cost associated with travels to and from the health facility for TB medication Accommodation Direct out-of-pocket payments for lodging Other: communication Direct out-of-pocket payments on mobile credit/phone calls Indirect Cost (productivity losses associate with the providing TB treatment support) Time spent on travel/ transportation Productive time spent travels to and from health facility for TB medications Time spent with TB patient Productive time spent with TB patient supervising/serving TB medications. Waiting Time Productive time spent at health facility waiting for TB medications Zarit Burden Interviews The psychological pain associated with the provision of TB treatment support Zarit burden interview scores Table 3 Socio-demographic characteristics of respondents (n = 385). Characteristics n( %) Age group ​ 18–24 13(3.4) 25–34 90(23.4) 35–44 174(45.2) 45–54 95(24.7) >54 13(3.4) Gender ​ Male 205(53.3) Female 180(46.8) Marital status ​ Never Married 66(17.1) Married 284(73.8) Widowed 23(6.0) Divorced/Separated 12(3.1) Religion ​ Christian 303(78.7) Non-Christian 82(21.3) Highest level of education ​ Primary 69(17.9) Junior High School 146(37.9) Senior High School 137(35.6) Tertiary (University) 33(8.6) Ethnicity ​ Dagaaba/Frafra/Mo 77(20.0) Akan 233(60.5) Others 75(19.5) Household size ​ Alone 22(5.7) <4 166(43.1) 4–5 154(40.0) 6–7 43(11.2) Type of occupation ​ Farming 214(55.6) Government employee 24(6.2) Private employee 58(15.0) Trading 67(17.4) Students 6(1.6) Unemployed 16(4.2) Sector of employment (363) ​ Formal sector 82(22.6) Informal sector 281(77.4) Monthly income ​ No income 22(5.7) <500 134(34.8) 500–750 148(38.4) 750–999 34(8.8) >999 47(12.2) Relationship with patient ​ Family member 276(71.7) Friend 75(19.5) Health worker 22(5.7) Spouse 12(3.1) District of Residence ​ Berekum Municipal 68(17.1) Dormaa Municipal 54(14.0) Jaman North 48(12.5) Jaman South 38(9.9) Sunyani Municipal 104(27.0) Tain 73(19.0) R.B. Bio et al. Health Policy and Technology 14 (2025) 101060 3 Table 4 Direct and Indirect Costs of Tuberculosis Treatment Support to the treatment supporters. Cost component N Cost (GHS) Cost (US$) Average cost (GHS) Average cost (US$) Cost profile ( %) Direct Cost ​ ​ ​ ​ ​ ​ Food 298 5237.0 982.6 17.8 3.3 14.6 Transportation 237 6011.0 1127.8 25.4 4.8 16.8 Others 197 736.0 138.1 3.7 0.7 2.1 Total direct cost ​ 11,984.0 2248.4 46.8 8.7 33.4 Indirect Cost ​ ​ ​ ​ ​ ​ Formal Sector 82 1530.9 287.2 18.7 3.5 4.3 Informal Sector 281 22,322.2 4188.0 79.4 14.9 62.3 Total Indirect Cost 363 23,853.2 4475.3 65.7 12.3 66.6 TOTAL COST ​ 35,837.2 6723.7 112.4 21.1 100 Table 5 Predictors of Tuberculosis Treatment Support Costs. Total direct cost Total indirect cost Total cost Joint effect Characteristics β [95 % CI] β [95 % CI] β [95 % CI] F-stat; P-value Age − 0.1 [− 0.2, 0.1] 0.0 [− 0.1, 0.2] 0.0 [− 0.3, 0.2] 0.4; 0.641 Gender ​ ​ ​ 2.7; 0.100 Male 0.0 (reference) 0.0 (reference) 0.0 (reference) Female 4.0 [− 0.8, 8.8] − 27.1 [− 32.4, − 21.8] *** − 23.1 [− 30.7, − 15.5] *** Marital status ​ ​ ​ Never married 0.0 (reference) 0.0 (reference) 0.0 (reference) 3.0; 0.029 * Married 2.8 [− 2.9, 8.6] 29.2 [22.9, 35.6] *** 32.1 [23.0, 41.2] *** Widowed 26.0 [7.1, 44.8] ** − 42.0 [− 62.9, − 21.0] *** − 16.0 [− 46.0, 14.0] Divorce − 2.1 [− 11.6, 7.3] 38.4 [27.9, 48.9] *** 36.2 [21.2, 51.3] *** Highest education ​ ​ ​ 4.7; 0.003 ** Primary 0.0 (reference) 0.0 (reference) 0.0 (reference) Junior high 13.1 [− 4.8, 30.9] − 8.2 [− 28.1, 11.6] 4.8 [− 23.5, 33.2] Senior high 15.2 [− 2.8, 33.1] − 19.6 [− 39.6, 0.3] − 4.4 [− 33.0, 24.1] Tertiary 12.1 [5.2, 19.0] ** − 48.6 [− 56.3, − 40.9] *** − 36.5 [− 47.5, − 25.6] *** Household size 1.1 [0.2, 2.0] * 1.4 [0.4, 2.4] ** 2.5 [1.1, 3.9] *** 6.2; 0.002 ** Monthly income (₵₵100) 0.0 [− 1.0, 0.9] − 4.1 [− 5.2, − 3.0] *** − 4.2 [− 5.7, − 2.6] *** 28.7; <0.001*** District ​ ​ ​ 7.2; <0.001*** Berekum 0.0 (reference) 0.0 (reference) 0.0 (reference) Dormaa 6.3 [2.3, 10.4] ** − 1.2 [− 5.7, 3.3] 5.1 [− 1.3, 11.6] Jaman North 4.8 [0.5, 9.1] * − 1.9 [− 6.7, 2.8] 2.9 [− 3.9, 9.7] Jaman South − 4.7 [− 9.2, − 0.2] * − 4.7 [− 9.7, 0.3] − 9.4 [− 16.6, − 2.2] * Sunyani − 1.8 [− 5.2, 1.7] − 0.3 [− 4.1, 3.6] − 2.0 [− 7.5, 3.5] Tain 3.1 [− 0.6, 6.9] − 0.8 [− 5.0, 3.3] 2.3 [− 3.6, 8.3] β: adjusted coefficient. CI: confidence interval. *: p < 0.05. **: p < 0.01. ***: p < 0.001. R.B. Bio et al. Health Policy and Technology 14 (2025) 101060 4 Predictors of tuberculosis treatment support costs The study reveals disparities in TB treatment costs based on de mographics and location (Table 5). Widows face significantly higher average direct costs (GHS 26.0, 95 % CI: GHS [7.1, 44.8]) than un married individuals. Those with tertiary education experience elevated costs (GHS 12.1, 95 % CI: GHS [5.2, 19.0]) compared to primary edu cation. An increase in household member’s correlates with a GHS 1.1 rise in total direct costs (95 % CI: GHS [0.2, 2.0]). Regionally, Dormaa and Jaman North incur higher costs (GHS 6.3, 95 % CI: GHS [2.3, 10.4]; GHS 4.8, 95 % CI: GHS [0.5, 9.1]) compared to Berekum District, while Jaman South sees lower costs (GHS 4.7, 95 % CI: GHS [− 9.2, − 0.2]). Multivariate regression emphasizes the significant impact of marital status, education level, household size, income, and district on TB treatment support costs among respondents’ Predictors of Zarit Burden interview scores Table 6 presents one-way ANOVA and Welch’s t-test results for socio- demographic characteristics of TB treatment support recipients. Signif icant differences in mean Zarit Burden scores were found by sex (T=− 4.9, p < 0.001), marital status (F = 16.1, p < 0.001), education (F = 31.2, p < 0.001), and income (F = 12.7, p < 0.001). In the multiple linear regression model, females had an average score 3.0 points higher than males (95 % CI: [2.2, 3.7]). Widowed (− 6.5, 95 % CI: [− 9.0, − 4.0]) and divorced (− 7.8, 95 % CI: [− 9.1, − 6.6]) individuals had significantly Fig. 1. Mean Zarit Burden Score for each Subscale of the 12 Items Fig. 1 displays mean scores for Zarit Burden Items. Those lacking personal time had the lowest mean (1.6/4), while respondents with health issues and strained relationships scored highest (2.1/4 each). Fig. 2. Distribution of Treatment Supporters’ Level of Burden by Zarit Inter view ScoreTop of Form Treatment Supporters’ burden levels were assessed using Zarit burden inter view scores. Scores 0 to >10 indicated no to mild burden, 10–20 indicated mild to moderate, and >20 indicated high burden25. Findings revealed 16.1 % experiencing moderate burden, while 77.1 % had high burden among treatment supporters, as depicted in Fig. 2. R.B. Bio et al. Health Policy and Technology 14 (2025) 101060 5 lower burden scores. Differences were observed by education and household size. Increasing direct cost by GHS100 led to a 3.1-point in crease (95 % CI: [1.7, 4.4]) in Zarit Burden score, and a GHS100 increase in indirect cost led to a 13.7-point increase (95 % CI: [11.1, 16.3]) in Zarit Burden score. Discussion Supporting tuberculosis patients with treatment costs averages GHS 122.4 (US$21.1) monthly, covering travel, feeding, and indirect ex penses. Travel costs vary based on factors like frequency, transportation mode, and proximity to health facilities, imposing costs. Direct costs, particularly feeding, are noteworthy, while indirect costs, tied to time loss, constitute the highest burden. Socio-demographic factors such as marital status, education, household size, income, and district contribute to support costs. Dormaa and Jaman North residents face higher costs (GHS6.3 and GHS4.8, respectively), potentially due to distant travel for tuberculosis treatment. This aligns with studies in Ethiopia [1] and Zambia [25] linking rural residency to increased tuberculosis treatment expenses. Within Ghana, regional disparities in economic opportunities, healthcare infrastructure, and social support systems may influence the extent and nature of costs incurred by treatment supporters. For treat ment supporters in rural regions, the costs of accompanying patients to health facilities can be substantial. Costs may include transportation expenses, lost earnings due to time away from work if treatment centres are far from home. In contrast, urban settings may offer shorter travel distances and better access to public transportation, reducing some of these costs. However, urban areas may present other challenges, such as high out-of-pocket costs for services and congestion-related delays. Findings from the Bono Region can be applied to other regions by identifying common public health challenges, health system structures, and socio-cultural factors influencing access to health care. While spe cific contextual differences exist, broader themes such as access to healthcare, health-seeking behaviors, community engagement, and the effectiveness of interventions can inform strategies in similar settings. However, adjustments may be necessary to account for variations in infrastructure, population demographics, and policy implementation across regions. Education independently predicts total direct costs, with tertiary- educated individuals incurring GHS12.1 (95 % CI: GHS [5.2, 19.0]) more than those with primary education, consistent with findings in Nigeria [26] and Benin [27]. Larger household sizes independently contribute to higher treatment-related expenses, corroborating a sys tematic review anticipating elevated healthcare costs in developing countries [28]. Regarding psychosocial burden, assessed via the Zarit burden scale, significant burdens were observed, indicating notable social and psy chological challenges leading to supporter fatigue. This aligns with global and Ghanaian research, emphasizing caregiver strain in chronic diseases like TB [19,29]. In Ghana, 72 % of family caregivers faced substantial burden, consistent with cultural expectations [29]. Pre dictors of intangible costs included gender, marital status, religion, ed ucation, ethnicity, income, and the relationship with TB patients. Females exhibited a significantly higher burden (3.0 [95 % CI: 2.2, 3.7]) than male supporters, consistent with Ghana and Nigeria’s findings [30, 31]. The regression model revealed a significant association between increased direct and indirect costs of assisting TB patients and higher Zarit Burden scores. A GHS100 rise in direct costs led to a 3.1 (95 % CI: [1.7, 4.4]) increase, while a similar increase in indirect costs resulted in a 13.7 (95 % CI: [11.1, 16.3]) rise in Zarit Burden scores. Consistent with past studies, economic burdens on family caregivers in Canada [32] were linked to higher caregiving burden. The findings on the costs and psychosocial burden of TB to treatment supporters in the Bono Region have significant policy implications. Table 6 Predictors of Zarit Burden Interview Scores. Zarit score Linear regression of Zarit score Characteristics Mean ± SD F-stat; P- value aβ [95 % CI] Age group ​ 1.2; 0.332 ​ ​ 18–24 23.5 ± 3.4 ​ ​ 0.0 [reference] 25–34 22.7 ± 2.7 ​ ​ 0.0 [− 0.8, 0.9] 35–44 22.3 ± 3.3 ​ ​ 0.2 [− 0.6, 1.0]s 45–54 22.7 ± 2.8 ​ ​ 0.3 [− 0.5, 1.2] >54 21.4 ± 2.8 ​ ​ − 0.6 [− 1.7, 0.5] Sex ​ − 4.9; <0.001 *** ​ ​ Male 21.8 ± 2.4 ​ ​ 0.0 [reference] Female 23.3 ± 3.5 ​ ​ 3.0 [2.2, 3.7] *** Marital status ​ 16.1; <0.001 *** ​ ​ Never married 22.0 ± 2.9 ​ ​ 0.0 [reference] Married 23.0 ± 3.0 ​ ​ 0.7 [− 0.3, 1.8] Widowed 19.0 ± 1.6 ​ ​ − 6.5 [− 9.0, − 4.0] *** Divorce 21.0 ± 0.0 ​ ​ − 7.8 [− 9.1, − 6.6] *** Highest education ​ 31.2; <0.001 *** ​ ​ Primary 20.7 ± 2.7 ​ ​ 0.0 [reference] Junior high 21.7 ± 2.8 ​ ​ − 8.7 [− 10.9, − 6.4] *** Senior high 24.0 ± 3.0 ​ ​ − 5.7 [− 8.0, − 3.4] *** Tertiary 23.9 ± 0.3 ​ ​ − 6.1 [− 7.7, − 4.6] *** Household size ​ 2.1; 0.094 ​ ​ Alone 24.0 ± 0.0 ​ ​ 0.0 [reference] <4 22.5 ± 3.0 ​ ​ − 8.3 [− 11.6, − 5.0] *** 4–5 22.4 ± 3.2 ​ ​ − 8.3 [− 11.6, − 5.0] *** 6–7 22.1 ± 3.1 ​ ​ − 8.8 [− 12.1, − 5.5] *** Monthly income ​ 12.7; <0.001 *** ​ ​ No income 24.0 ± 0.0 ​ ​ 0.0 [reference] <500 21.2 ± 3.0 ​ ​ − 4.8 [− 5.8, − 3.9] *** 500–750 23.3 ± 3.3 ​ ​ − 0.5 [− 1.3, 0.3] 750–999 21.8 ± 3.1 ​ ​ − 0.2 [− 1.5, 1.1] >999 23.5 ± 0.5 ​ ​ ​ District ​ 0.3; 0.890 ​ ​ Berekum 22.8 ± 3.3 ​ ​ 0.0 [reference] Derma 22.5 ± 2.9 ​ ​ 0.1 [− 0.4, 0.6] Jaman North 22.2 ± 3.5 ​ ​ − 0.5 [− 1.1, 0.0] Jaman South 22.8 ± 2.4 ​ ​ 0.3 [− 0.2, 0.9] Sunyani 22.6 ± 2.9 ​ ​ 0.2 [− 0.3, 0.6] Tain 22.3 ± 3.2 ​ ​ − 0.2 [− 0.7, 0.3] (continued on next page) R.B. Bio et al. Health Policy and Technology 14 (2025) 101060 6 Costs, including transportation costs, loss of income, and out-of-pocket expenses, highlight the need for economic support mechanisms such as subsidies, financial incentives, and reimbursement programs [33]. Integrating TB-related financial support into broader social protection initiatives could provide a safety net for caregivers facing economic hardships. The study also underscores the psychosocial burdens, such as emotional distress and disruptions to personal life. These findings sug gest that psychosocial support interventions, such as counselling ser vices and peer support networks through community engagement can enhance treatment adherence and improve the overall well-being of both patients and their treatment supporters. Addressing the Costs and psychosocial burden of TB to treatment supporters requires targeted policy interventions that provide financial relief, psychosocial support, and systemic improvements in healthcare delivery [34]. These measures will not only reduce the burden on treatment supporters but also contribute to better treatment outcomes and overall TB control efforts. Despite valuable insight into the economic and psychosocial burden borne by treatment supporters the generalizability of these findings beyond the Bono Region requires careful consideration, particularly when extrapolating to other countries or regions with different socio economic contexts. The Costs and psychosocial burden of TB treatment support are likely to differ in low, middle, and high-income country settings. In low- income countries with weak health systems, the economic costs on treatment supporters may be exacerbated by higher out-of-pocket costs, unreliable healthcare services, and limited social protection measures. For example, in some sub-Saharan African countries, long distances to healthcare facilities and high transportation costs may further strain household finances [3]. Additionally, cultural norms regarding care giving responsibilities could shape the experience of treatment sup porters differently across various societies [35]. In middle-income countries, while social protection schemes may exist, they may not fully cover the indirect costs associated with care giving, such as lost income and psychological distress [36,37]. The structure of healthcare financing, whether through out-of-pocket pay ments, national insurance, or donor-funded programs can significantly affect the costs borne by treatment supporters [38]. In high-income countries, where healthcare systems are more robust and social wel fare programs more extensive, the costs on treatment supporters may be lower. This study is the first to estimate direct, indirect, and psychosocial burden of tuberculosis treatment support in Ghana, offering valuable insights for policy and the goal to eradicate tuberculosis by 2035. However, limitations include a cross-sectional approach and reliance on the human capital method, neglecting individual earnings variations. Longitudinal methods could reflect better costs incurred by treatment supporters. Though the valuable insights generated by this study on the costs and psychosocial burden costs of assisting with TB treatment, some limita tions must be acknowledged. The study collected cross-sectional data, capturing a snapshot of costs at a particular time. However, the costs and psychosocial burden of TB treatment supporters may fluctuate over time due to changes in economic conditions Also, the study used a purposive sampling approach for the health facility selection, potentially limiting the representativeness of the findings. Given the diverse socioeconomic backgrounds of TB treatment supporters, the study sample may not fully capture variations in costs and experiences across different demographic groups. Additionally, the study was conducted in the Bono Region of Ghana, and the findings may not be directly applicable to other countries or regions where contextual factors such as healthcare infrastructure, economic conditions, and cultural practices may differ. Finally, the study relied on self-reported data to estimate the costs and psychosocial burden. Respondents may have experienced recall bias, particularly when recalling expenses or emotional burdens asso ciated with supporting TB patients. This may have led to underestima tion or overestimation of costs associated with TB treatment support. These limitations may impact the generalizability of the findings and should be considered in the interpretation and application of the results. Based on the findings and limitations of this study, several directions for future research are recommended. Future research should focus on longitudinal studies that will enable track the costs and psychosocial burden over the full course of treatment to provide more clearer picture of the economic burden associated tuberculosis treatment support. Given that socioeconomic conditions and health system structures vary across regions, comparative studies between urban and rural re gions, or across different administrative regions, would provide insights into the contextual factors influencing TB treatment support costs for region specific interventions. While this study highlights psychosocial costs of assisting TB patients with treatment, future research should employ qualitative methodolo gies such as in-depth interviews and focus group discussions to explore the live experiences of TB treatment supporters. Future studies should explore the cost-effectiveness of potential support mechanisms, such as cash transfers, transportation subsidies, or mental health counselling, to mitigate the economic and psychological burden on TB treatment supporters. To mitigate the costs and psychosocial burden of supporting TB treatment, Ghana Likelihood Empowerment against Poverty program (LEAP), has shown positive impacts on household access to health care, though its direct effects on caregiving require further study [39]. Inte grating treatment supporters into the LEAP program could help reduce the economic burden of support for TB treatment and improve treatment adherence. Also, transport and service vouchers, effective in Kenya and Bangladesh [40,41], could be adapted to the Ghanaian context. The National Health Insurance Scheme (NHIS) reduces direct service costs but inadequately addresses indirect costs like transport. Therefore, this study recommends Ghana Health Service and Ministry of Health, Ghana should advocate for integration of LEAP or transport voucher programs in the tuberculosis control program. Conclusion The study underscores the substantial financial burden on tubercu losis treatment supporters and recommends extending the livelihood empowerment against poverty program in Ghana to cover treatment support costs. Funding The authors confirm this study has no funding support. Competing interests The authors declare that they have no competing interests. Table 6 (continued ) Zarit score Linear regression of Zarit score Characteristics Mean ± SD F-stat; P- value aβ [95 % CI] Total direct cost (₵₵100) ​ ​ ​ 3.1 [1.7, 4.4] *** Total indirect cost (₵₵100) ​ ​ ​ 13.7 [11.1, 16.3] *** SD: standard deviation. aβ: adjusted coefficient. CI: confidence interval. *: p < 0.05. **: p < 0.01. ***: p < 0.001. R.B. Bio et al. Health Policy and Technology 14 (2025) 101060 7 Ethical approval All ethical standards and procedures involving human subjects was followed in conducting the study. Before taking part in the study, each participant signed the informed consent form to provide their informed consent for inclusion. The protocol for this study was reviewed and approved by Ghana Health Service Ethics Review Committee with reference number GHS-ERC 003/03/2019. Acknowledgements The study team acknowledges faculty members of the School of Public Health, University of Ghana for the contributions made in enhancing the study protocol. We also acknowledge all tuberculosis treatment supporters who provided the data. CRediT authorship contribution statement Robert Bagngmen Bio: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Supervi sion, Visualization, Writing – original draft, Writing – review & editing. Patricia Akweongo: Investigation, Methodology, Writing – review & editing, Supervision. John Azaare: Formal analysis, Writing – review & editing. Francis Adane: Data curation, Writing – review & editing. Kasim Abdulai: Software, Validation, Writing – review & editing. Richard Ali Laar: Writing – review & editing, Investigation. Abraham Titiati: Writing – review & editing, Investigation. References [1] Awoke N, Dulo B, Wudneh F. Total delay in treatment of tuberculosis and associated factors among new pulmonary TB patients in selected health facilities of Gedeo zone. Southern Ethiopia; 2017. https://doi.org/10.1155/2019/2154240 [cited 2020 May 29];(18). 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Health Policy and Technology 14 (2025) 101060 9 https://academic.oup.com/heapol/article/32/suppl_4/iv48/2999103 https://academic.oup.com/heapol/article/32/suppl_4/iv48/2999103 http://pmc/articles/PMC6631110/ https://idpjournal.biomedcentral.com/track/pdf/10.1186/s40249-015-0059-8 https://idpjournal.biomedcentral.com/track/pdf/10.1186/s40249-015-0059-8 http://refhub.elsevier.com/S2211-8837(25)00088-7/sbref0040 http://refhub.elsevier.com/S2211-8837(25)00088-7/sbref0040 https://doi.org/10.1371/journal.pone.0256067 https://doi.org/10.1371/journal.pone.0256067 http://refhub.elsevier.com/S2211-8837(25)00088-7/sbref0042 http://refhub.elsevier.com/S2211-8837(25)00088-7/sbref0042 http://refhub.elsevier.com/S2211-8837(25)00088-7/sbref0042 http://refhub.elsevier.com/S2211-8837(25)00088-7/sbref0042 Costs and psychosocial burden of tuberculosis to the treatment supporters in Ghana Introduction Methods Study setting Inclusion and exclusion criteria Sampling procedure Data collection Description of costs variables Scoring of the Zarit Burden scale Data analysis Results Direct and indirect costs of tuberculosis treatment support Predictors of tuberculosis treatment support costs Predictors of Zarit Burden interview scores Discussion Conclusion Funding Competing interests Ethical approval Acknowledgements CRediT authorship contribution statement References