A SARS-CoV-2 Surveillance System in Sub-Saharan Africa: Modeling Study for Persistence and Transmission to Inform Policy

• DOI: 10.2196/24248
• Publication Date: 2020-10-23T01:10:08Z
• Authors: Lori Ann Post; Salem T Argaw; Cameron Jones; Charles B Moss; Danielle Resnick; Lauren Nadya Singh; Robert Leo Murphy; Chad J Achenbach; Janine White; Tariq Ziad Issa; Michael J Boctor; James Francis Oehmke
• Keywords: Public health surveillance; Disease Surveillance

Background Since the novel coronavirus emerged in late 2019, scientific and public health community around world have sought to better understand, surveil, treat, prevent disease, COVID-19. In sub-Saharan Africa (SSA), many countries responded aggressively decisively with lockdown measures border closures. Such actions may helped large outbreaks throughout much of region, though there is substantial variation caseloads mortality between nations. Additionally, system infrastructure remains a concern SSA, threaten increase poverty food insecurity for subcontinent’s poorest residents. The lack sufficient testing, asymptomatic infections, poor reporting practices limit our understanding virus’s impact, creating need more accurate surveillance metrics that account underreporting data contamination. Objective goal this study improve infectious disease by complementing standardized new decomposable COVID-19 overcome limitations contamination inherent systems. addition prevalence observed daily cumulative testing positivity rates, morbidity, mortality, we derived transmission terms speed, acceleration or deceleration, change deceleration (jerk), 7-day rate persistence, which explains where how rapidly transmitting quantifies shifts inform policies mitigate SSA. Methods We extracted 60 days from registries employed an empirical difference equation measure case numbers 47 as function prior number cases, level weekly shift variables based on dynamic panel model was estimated using generalized method moments approach implementing Arellano-Bond estimator R. Results Kenya, Ghana, Nigeria, Ethiopia, South most cases COVID-19, Seychelles, Eritrea, Mauritius, Comoros, Burundi fewest. contrast, acceleration, jerk, persistence indicate rates transmissions differ cases. September 2020, Cape Verde, Namibia, Eswatini, had highest speed at 13.1, 7.1, 3.6, 3 infections per 100,0000, respectively; Zimbabwe transmission, while Zambia largest week compared last week, referred jerk. Finally, indicates 15, are 8, decreased 216.7 173.2 Ethiopia 136.7 106.3 100,000. statistical validated regression results; they determined recent changes pattern infection, during weeks 1-8 9-15, were country differences evolution SSA pandemic. This represents decrease R value consistent de-escalation pandemic African continent general. Conclusions Standard such deaths necessary but insufficient transmission. Public leaders also know accelerating decelerating, whether those over short time frames because can quickly escalate, today 7 ago. Even home some world, development population size not necessarily predictive meaning higher income like United States learn best implement mitigation prevention efforts. International Registered Report Identifier (IRRID) RR2-10.2196/21955