ABSTRACT
INTRODUCTION: COVID-19 has spread across the African continent, including Niger. Yet very little is known about the phenotype of people who tested positive for COVID-19. In this humanitarian crises region, we aimed at characterizing variation in clinical features among hospitalized patients with COVID-19-like syndrome and to determine predictors associated with COVID-19 mortality among those with confirmed COVID-19. METHODS: The study was a retrospective nationwide cohort of hospitalized patients isolated for COVID-19 infection, using the health data of the National Health Information System from 19 March 2020 (onset of the pandemic) to 17 November 2020. All hospitalized patients with COVID-19-like syndrome at admission were included. A Cox-proportional regression model was built to identify predictors of in-hospital death among patients with confirmed COVID-19. RESULTS: Sixty-five percent (472/729) of patients hospitalized with COVID-19 like syndrome tested positive for SARS-CoV-2 among which, 70 (15%) died. Among the patients with confirmed COVID-19 infection, age was significantly associated with increased odds of reporting cough (adjusted odds ratio [aOR] 1.02; 95% confidence interval [CI] 1.01-1.03) and fever/chills (aOR 1.02; 95% CI 1.02-1.04). Comorbidity was associated with increased odds of presenting with cough (aOR 1.59; 95% CI 1.03-2.45) and shortness of breath (aOR 2.03; 95% CI 1.27-3.26) at admission. In addition, comorbidity (adjusted hazards ratio [aHR] 2.04; 95% CI 2.38-6.35), shortness of breath at baseline (aHR 2.04; 95% CI 2.38-6.35) and being 60 years or older (aHR 5.34; 95% CI 3.25-8.75) increased the risk of COVID-19 mortality two to five folds. CONCLUSION: Comorbidity, shortness of breath on admission, and being aged 60 years or older are associated with a higher risk of death among patients hospitalized with COVID-19 in a humanitarian crisis setting. While robust prospective data are needed to guide evidence, our data might aid intensive care resource allocation in Niger.
ABSTRACT
INTRODUCTION: the COVID-19 pandemic has spread across all countries in Africa, with much of the model forecasting disastrous results owing to weak health services and political uncertainty. In Niger, an adaptive solution to the COVID-19 pandemic has been implemented by community-based surveillance system (CBS) to complement passive case-finding in health systems. METHODS: the CBS program was designed to use the current CBS polio network spanning 37 health districts in six regions. Between April and November 2020, 150 community health workers (CHWs) were equipped to improve integrated disease surveillance and response (IDSR) preparedness and response to the COVID-19 pandemic. We retrospectively analysed the health data of the National Health Information System to describe the effect of CBS in COVID-19 surveillance. RESULTS: overall, trained CHWs were able to raise awareness among 2,681,642 persons regarding COVID-19 preventions and controls strategies. They reported 143 (84%) valid alerts resulting in two positive COVID-19 cases missing in the community. In addition, CHWs added to the contact tracing of 37 individuals and informed about the deaths in the community. CONCLUSION: community-based surveillance improved COVID-19 response in Niger. Logistic assistance and ongoing training are the foundations for increasing and sustaining the sensitivity of CBS systems in response to the COVID-19 pandemic to deter hotspots across countries.