Assessing the impact of non-pharmaceutical interventions (NPIs) and BCG vaccine cross-protection in the transmission dynamics of SARS-CoV-2 in eastern Africa.

OBJECTIVE: The outbreak of the novel coronavirus disease 2019 (COVID-19) is still affecting African countries. The pandemic presents challenges on how to measure governmental, and community responses to the crisis. Beyond health risks, the socio-economic implications of the pandemic motivated us to examine the transmission dynamics of COVID-19 and the impact of non-pharmaceutical interventions (NPIs). The main objective of this study was to assess the impact of BCG vaccination and NPIs enforced on COVID-19 case-death-recovery counts weighted by age-structured population in Ethiopia, Kenya, and Rwanda. We applied a semi-mechanistic Bayesian hierarchical model (BHM) combined with Markov Chain Monte Carlo (MCMC) simulation to the age-structured pandemic data obtained from the target countries. RESULTS: The estimated mean effective reproductive number (Rt) for COVID-19 was 2.50 (C1: 1.99-5.95), 3.51 (CI: 2.28-7.28) and 3.53 (CI: 2.97-5.60) in Ethiopia, Kenya and Rwanda respectively. Our results indicate that NPIs such as lockdowns, and curfews had a large effect on reducing Rt. Current interventions have been effective in reducing Rt and thereby achieve control of the epidemic. Beyond age-structure and NPIs, we found no significant association between COVID-19 and BCG vaccine-induced protection. Continued interventions should be strengthened to control transmission of SARS-CoV-2.

Using outbreak data to estimate the dynamic COVID-19 landscape in Eastern Africa.

BACKGROUND: The emergence of COVID-19 as a global pandemic presents a serious health threat to African countries and the livelihoods of its people. To mitigate the impact of this disease, intervention measures including self-isolation, schools and border closures were implemented to varying degrees of success. Moreover, there are a limited number of empirical studies on the effectiveness of non-pharmaceutical interventions (NPIs) to control COVID-19. In this study, we considered two models to inform policy decisions about pandemic planning and the implementation of NPIs based on case-death-recovery counts. METHODS: We applied an extended susceptible-infected-removed (eSIR) model, incorporating quarantine, antibody and vaccination compartments, to time series data in order to assess the transmission dynamics of COVID-19. Additionally, we adopted the susceptible-exposed-infectious-recovered (SEIR) model to investigate the robustness of the eSIR model based on case-death-recovery counts and the reproductive number (R0). The prediction accuracy was assessed using the root mean square error and mean absolute error. Moreover, parameter sensitivity analysis was performed by fixing initial parameters in the SEIR model and then estimating R0, ß and γ. RESULTS: We observed an exponential trend of the number of active cases of COVID-19 since March 02 2020, with the pandemic peak occurring around August 2021. The estimated mean R0 values ranged from 1.32 (95% CI, 1.17-1.49) in Rwanda to 8.52 (95% CI: 3.73-14.10) in Kenya. The predicted case counts by January 16/2022 in Burundi, Ethiopia, Kenya, Rwanda, South Sudan, Tanzania and Uganda were 115,505; 7,072,584; 18,248,566; 410,599; 386,020; 107,265, and 3,145,602 respectively. We show that the low apparent morbidity and mortality observed in EACs, is likely biased by underestimation of the infected and mortality cases. CONCLUSION: The current NPIs can delay the pandemic pea and effectively reduce further spread of COVID-19 and should therefore be strengthened. The observed reduction in R0 is consistent with the interventions implemented in EACs, in particular, lockdowns and roll-out of vaccination programmes. Future work should account for the negative impact of the interventions on the economy and food systems.

Modelling and projections of the COVID-19 epidemic and the potential impact of social distancing in Cameroon.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19) pandemic continues to be a global health problem with a significant impact in Cameroon. The aim of this study was to improve the understanding of the spread of COVID-19 and enhance disease control strategies. We assessed the SIRD (susceptible, infected, recovered and death) model to describe COVID-19 reported cases in Cameroon from March 7 to May 31, 2020, and study the impact of social distancing. We assessed changes in the basic reproduction number (R0) on a phaseadjusted process and forecasted the longterm epidemic trend. Daily incidence data was fitted to a log-linear model before each peak of the epidemic with the purpose of studying the effective mechanism of variation of the reproduction number Re. Before the first peak of the epidemic, R0 was estimated as 6.8. Social distancing and restricted measures contributed to reduce the value to 3.24 by April 30 but remained greater than 1 (R0=2.43) by May 22 when the initial measures implemented by the government to control the spread of the disease were relaxed. The estimated number of infections ranged 13,703-18,456 by May 31, and will continue increasing throughout June 2020 with more than 20,000 cases expected by the end of June 2020, suggesting that the pandemic is still in the growth phase. Longterm prediction showed a flattened curve towards April 2021. Preventive measures initially implemented by the government of Cameroon should be strictly maintained and reinforced to reduce Re to 0.5.