Unintended consequences of implementing non-pharmaceutical interventions for the COVID-19 response in Africa: experiences from DRC, Nigeria, Senegal, and Uganda.

INTRODUCTION: The coronavirus (COVID 19) pandemic is one of the most terrifying disasters of the twenty-first century. The non-pharmaceutical interventions (NPIs) implemented to control the spread of the disease had numerous positive consequences. However, there were also unintended consequences-positively or negatively related to the nature of the interventions, the target, the level and duration of implementation. This article describes the unintended economic, Psychosocial and environmental consequences of NPIs in four African countries. METHODS: We conducted a mixed-methods study in the Democratic Republic of Congo (DRC), Nigeria, Senegal and Uganda. A comprehensive conceptual framework, supported by a clear theory of change was adopted to encompass both systemic and non-systemic interventions. The data collection approaches included: (i) review of literature; (ii) analysis of secondary data for selected indicators; and (ii) key informant interviews with policy makers, civil society, local leaders, and law enforcement staff. The results were synthesized around thematic areas. RESULTS: Over the first six to nine months of the pandemic, NPIs especially lockdowns, travel restrictions, curfews, school closures, and prohibition of mass gathering resulted into both positive and negative unintended consequences cutting across economic, psychological, and environmental platforms. DRC, Nigeria, and Uganda observed reduced crime rates and road traffic accidents, while Uganda also reported reduced air pollution. In addition, hygiene practices have improved through health promotion measures that have been promoted for the response to the pandemic. All countries experienced economic slowdown, job losses heavily impacting women and poor households, increased sexual and gender-based violence, teenage pregnancies, and early marriages, increased poor mental health conditions, increased waste generation with poor disposal, among others. CONCLUSION: Despite achieving pandemic control, the stringent NPIs had several negative and few positive unintended consequences. Governments need to balance the negative and positive consequences of NPIs by anticipating and instituting measures that will support and protect vulnerable groups especially the poor, the elderly, women, and children. Noticeable efforts, including measures to avoid forced into marriage, increasing inequities, economic support to urban poor; those living with disabilities, migrant workers, and refugees, had been conducted to mitigate the negative effects of the NIPs.

COVID-19 Vaccine Attitude and Its Predictors Among People Living With Chronic Health Conditions in Ibadan, Nigeria.

Objective: To assess vaccination attitude and its associated factors among people with chronic health conditions. Methods: In this cross-sectional study, participants were 423 patients with chronic medical conditions. Data were collected on socio-demographic and COVID-19-related characteristics, via Open Data Kit software. A Vaccination Attitudes Examination (VAX) Scale was adopted. The main outcome was vaccine attitude status defined as positive if a VAX sum score was above the median value; otherwise, non-positive. Data were analysed using Chi-square and multivariate logistic regression analyses, at 5% level of significance. Results: Overall proportion of patients with a positive attitude towards COVID-19 vaccination uptake was 46.6%. The most influential factor towards positive attitude was rating the government high in handling the pandemic. Other factors were education, income, COVID-19 knowledge and living room arrangement (p < 0.05). Conclusion: Less than half of people living with a chronic medical condition had a positive attitude towards the COVID-19 vaccine. The attitudes are strongly mediated by confidence in the government. The government could promote a positive vaccine attitude by improving the clarity of health instructions that shows government transparency and effective communication. These are critical tools for maintaining public trust and confidence.

COVID-19 surveillance in Democratic Republic of Congo, Nigeria, Senegal and Uganda: strengths, weaknesses and key Lessons.

INTRODUCTION: As part of efforts to rapidly identify and care for individuals with COVID-19, trace and quarantine contacts, and monitor disease trends over time, most African countries implemented interventions to strengthen their existing disease surveillance systems. This research describes the strengths, weaknesses and lessons learnt from the COVID-19 surveillance strategies implemented in four African countries to inform the enhancement of surveillance systems for future epidemics on the continent. METHODS: The four countries namely the Democratic Republic of Congo (DRC), Nigeria, Senegal, and Uganda, were selected based on their variability in COVID-19 response and representation of Francophone and Anglophone countries. A mixed-methods observational study was conducted including desk review and key informant interviews, to document best practices, gaps, and innovations in surveillance at the national, sub-national, health facilities, and community levels, and these learnings were synthesized across the countries. RESULTS: Surveillance approaches across countries included - case investigation, contact tracing, community-based, laboratory-based sentinel, serological, telephone hotlines, and genomic sequencing surveillance. As the COVID-19 pandemic progressed, the health systems moved from aggressive testing and contact tracing to detect virus and triage individual contacts into quarantine and confirmed cases, isolation and clinical care. Surveillance, including case definitions, changed from contact tracing of all contacts of confirmed cases to only symptomatic contacts and travelers. All countries reported inadequate staffing, staff capacity gaps and lack of full integration of data sources. All four countries under study improved data management and surveillance capacity by training health workers and increasing resources for laboratories, but the disease burden was under-detected. Decentralizing surveillance to enable swifter implementation of targeted public health measures at the subnational level was a challenge. There were also gaps in genomic and postmortem surveillance including community level sero-prevalence studies, as well as digital technologies to provide more timely and accurate surveillance data. CONCLUSION: All the four countries demonstrated a prompt public health surveillance response and adopted similar approaches to surveillance with some adaptations as the pandemic progresses. There is need for investments to enhance surveillance approaches and systems including decentralizing surveillance to the subnational and community levels, strengthening capabilities for genomic surveillance and use of digital technologies, among others. Investing in health worker capacity, ensuring data quality and availability and improving ability to transmit surveillance data between and across multiple levels of the health care system is also critical. Countries need to take immediate action in strengthening their surveillance systems to better prepare for the next major disease outbreak and pandemic.

COVID-19 Vaccine Attitude and Its Predictors Among People Living With Chronic Health Conditions in Ibadan, Nigeria

Objective: To assess vaccination attitude and its associated factors among people with chronic health conditions. Methods: In this cross-sectional study, participants were 423 patients with chronic medical conditions. Data were collected on socio-demographic and COVID-19-related characteristics, via Open Data Kit software. A Vaccination Attitudes Examination (VAX) Scale was adopted. The main outcome was vaccine attitude status defined as positive if a VAX sum score was above the median value;otherwise, non-positive. Data were analysed using Chi-square and multivariate logistic regression analyses, at 5% level of significance. Results: Overall proportion of patients with a positive attitude towards COVID-19 vaccination uptake was 46.6%. The most influential factor towards positive attitude was rating the government high in handling the pandemic. Other factors were education, income, COVID-19 knowledge and living room arrangement (p < 0.05). Conclusion: Less than half of people living with a chronic medical condition had a positive attitude towards the COVID-19 vaccine. The attitudes are strongly mediated by confidence in the government. The government could promote a positive vaccine attitude by improving the clarity of health instructions that shows government transparency and effective communication. These are critical tools for maintaining public trust and confidence.

Predictors and time to recovery from COVID-19 among patients attended at the treatment centers in Ekiti State, South West, Nigeria.

Introduction: time to clinical recovery from COVID-19 infection and associated factors has not been explored in Nigeria. This study was conducted to assess the predictors and time to recovery from COVID-19 among patients attended to at the treatment centers in Ekiti State, South West. Methods: a facility-based retrospective cohort study was conducted between March 2020 to October 2021. Laboratory confirmed COVID-19 positive test result of 586 patients receiving treatment at the treatment centres in Ekiti were included. Data were extracted from COVID-19 intake forms and medical records of patients. Data were analysed using descriptive statistics and survival analysis methods including Cox proportional hazards regression model. Level of significance was set at 5%. Results: the mean age of the patients was 43.46 (SD 0.74) years. Forty-seven percent (47%) of the patients were aged 25-44 years, fifty-one percent (51%) were males. The median recovery time of COVID-19 patients was 21 days (IQR: 14-23). Being a male-patient (95% CI 20.46-21.54), older age (95% CI 20.14-21.86), not admitted in the hospital (95% CI 22.74-23.26), and associated multiple co-morbidities (95% CI 17.65-28.35) were associated with delayed recovery time. Predictors of recovery time of patients from COVID-19 infection were admission status (aHR: 0.71, 95%CI 0.56-0.88; p=0.002) and symptoms on admission (aHR: 0.81, 95%CI 0.66-0.99; p=0.020). Conclusion: patients with comorbidities, older and those not admitted were more likely to have a delayed clinical recovery from COVID-19. Knowledge of the predictors might help health professionals in risk stratification and better management of patients with COVID-19.

Situation assessment and natural dynamics of COVID-19 pandemic in Nigeria, 31 May 2020.

BACKGROUND: The coronavirus disease (COVID-19) remains a global public health issue due to its high transmission and case fatality rate. There is apprehension on how to curb the spread and mitigate the socio-economic impacts of the pandemic, but timely and reliable daily confirmed cases' estimates are pertinent to the pandemic's containment. This study therefore conducted a situation assessment and applied simple predictive models to explore COVID-19 progression in Nigeria as at 31 May 2020. METHODS: Data used for this study were extracted from the websites of the European Centre for Disease Control (World Bank data) and Nigeria Centre for Disease Control. Besides descriptive statistics, four predictive models were fitted to investigate the pandemic natural dynamics. RESULTS: The case fatality rate of COVID-19 was 2.8%. A higher number of confirmed cases of COVID-19 was reported daily after the relaxation of lockdown than before and during lockdown. Of the 36 states in Nigeria, including the Federal Capital Territory, 35 have been affected with COVID-19. Most active cases were in Lagos (n = 4064; 59.2%), followed by Kano (n = 669; 9.2%). The percentage of COVID-19 recovery in Nigeria (29.5%) was lower compared to South Africa (50.3%), but higher compared to Kenya (24.1%). The cubic polynomial model had the best fit. The projected value for COVID-19 cumulative cases for 30 June 2020 in Nigeria was 27,993 (95% C.I: 27,001-28,986). CONCLUSION: The daily confirmed cases of COVID-19 are increasing in Nigeria. Increasing testing capacity for the disease may further reveal more confirmed cases. As observed in this study, the cubic polynomial model currently offers a better prediction of the future COVID-19 cases in Nigeria.