Department of Statistics
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Item SARS‑CoV‑2 incidence monitoring and statistical estimation of the basic and time‑varying reproduction number at the early onset of the pandemic in 45 sub‑Saharan African countries(BMC Public Health, 2024) Oduro, M.S.; Arhin‑Donkor, S.; Asiedu, L.; Kadengye, D.T.; Iddi, S.The world battled to defeat a novel coronavirus 2019 (SARS-CoV-2 or COVID-19), a respiratory illness that is transmitted from person to person through contacts with droplets from infected persons. Despite efforts to disseminate preventable messages and adoption of mitigation strategies by governments and the World Health Organization (WHO), transmission spread globally. An accurate assessment of the transmissibility of the coronavirus remained a public health priority for many countries across the world to fight this pandemic, especially at the early onset. In this paper, we estimated the transmission potential of COVID-19 across 45 countries in sub-Saharan Africa using three approaches, namely, R0 based on (i) an exponential growth model (ii) maximum likelihood (ML) estimation and (iii) a time-varying basic reproduction number at the early onset of the pandemic. Using data from March 14, 2020, to May 10, 2020, sub-Saharan African countries were still grappling with COVID-19 at that point in the pandemic. The region’s basic reproduction number ( R0 ) was 1.89 (95% CI: 1.767 to 2.026) using the growth model and 1.513 (95% CI: 1.491 to 1.535) with the maximum likelihood method, indicating that, on average, infected individuals transmitted the virus to less than two secondary persons. Several countries, including Sudan ( R0 : 2.03), Ghana ( R0 : 1.87), and Somalia ( R0 : 1.85), exhibited high transmission rates. These findings highlighted the need for continued vigilance and the implementation of effective control measures to combat the pandemic in the region. It is anticipated that the findings in this study would not only function as a historical record of reproduction numbers during the COVID-19 pandemic in African countries, but can serve as a blueprint for addressing future pandemics of a similar nature.Item Best-worst scaling in studying the impact of the coronavirus pandemic on health professionals in Ghana(Model Assisted Statistics and Applications, 2023) Nyarko, E.; Arku, D.; Duah, G.In this study, we utilized a best-worst scaling experiment design to assess the potential factors associated with depression, anxiety, and stress among health professionals following the experience of the COVID-19 pandemic. The maximum difference model was performed to analyze the potential risk factors associated with depression, anxiety, and stress. As a case study, a total of 300 health professionals in Ghana were included in the survey. The majority, 112 (68.7%) male health professionals and 97 (70.8%) female health professionals reported that they had encountered suspected COVID-19 patients. 83 (50.9%) of the male health professionals and 76 (55.5%) of the female health professionals reported that they had encountered confirmed COVID-19 patients. A considerable proportion of the males 59 (36.2%) and females 57 (41.6%) health professionals reported coming into direct contact with COVID-19 lab specimens. The findings indicated that a high proportion of health professionals encountered suspected or confirmed COVID-19 patients, while a considerable proportion had direct contact with COVID-19 lab specimens leading to psychological problems. Risk factors such as contact with confirmed COVID-19 patients, the relentless spread of the coronavirus, death of patients and colleagues, shortage of medical protective equipment, direct contact with COVID-19 lab specimens, and the permanent threat of being infected should be given special attention, and necessary psychological intervention provided for health professionals endorsing these risk factors. Improving the supply of medical protective equipment to meet occupational protection practices, sufficient rest, and improving the vaccination of the population might help safeguard health professionals from depression, anxiety, and stress. Our results provide insight into policy discussions on the mental health of health professionals and interventions that are essential to enhance psychological resilience.Item RNA-Seq of untreated wastewater to assess COVID-19 and emerging and endemic viruses for public health surveillance(Elsevier Ltd, 2023) Stockdale, S.R.; Blanchard, A.M.; Acheampong, E.; et al.Background The COVID-19 pandemic showcased the power of genomic sequencing to tackle the emergence and spread of infectious diseases. However, metagenomic sequencing of total microbial RNAs in wastewater has the potential to assess multiple infectious diseases simultaneously and has yet to be explored. Methods A retrospective RNA-Seq epidemiological survey of 140 untreated composite wastewater samples was performed across urban (n = 112) and rural (n = 28) areas of Nagpur, Central India. Composite wastewater samples were prepared by pooling 422 individual grab samples collected prospectively from sewer lines of urban municipality zones and open drains of rural areas from 3rd February to 3rd April 2021, during the second COVID-19 wave in India. Samples were pre-processed and total RNA was extracted prior to genomic sequencing. Findings This is the first study that has utilised culture and/or probe-independent unbiased RNA-Seq to examine Indian wastewater samples. Our findings reveal the detection of zoonotic viruses including chikungunya, Jingmen tick and rabies viruses, which have not previously been reported in wastewater. SARS-CoV-2 was detectable in 83 locations (59%), with stark abundance variations observed between sampling sites. Hepatitis C virus was the most frequently detected infectious virus, identified in 113 locations and co-occurring 77 times with SARS-CoV-2; and both were more abundantly detected in rural areas than urban zones. Concurrent identification of segmented virus genomic fragments of influenza A virus, norovirus, and rotavirus was observed. Geographical differences were also observed for astrovirus, saffold virus, husavirus, and aichi virus that were more prevalent in urban samples, while the zoonotic viruses chikungunya and rabies, were more abundant in rural environments. Interpretation RNA-Seq can effectively detect multiple infectious diseases simultaneously, facilitating geographical and epidemiological surveys of endemic viruses that could help direct healthcare interventions against emergent and pre-existent infectious diseases as well as cost-effectively and qualitatively characterising the health status of the population over time.