Tropicalisation of epidemiological models in Africa: A mixed and hybrid approach to better predict COVID‐19 indicators

Abstract

Context: Since the outbreak of the SARS-COV2 epidemic turned into a COVID-19 pandemic, international bodies such as the WHO as well as governments have announced projections for morbidity and mortality indicators related to COVID-19. Most of them indicated that the health situation would be worrying.Although using artificial intelligence with mathematical algorithms and/or neural networks, the results of the SIR models were poorly performing and not very accurate in relation to the observed reality in the African states in general and in Senegal in particular. Hence the imperative need to configure the modelling process and approach considering local contexts. Method: The model implemented is a mixed prediction model based on the Bucky model developed by OCHA and adapted to the context.The construction of the mixed model was done in two steps (basic model with publicly available data, such as those from United Nations-like organisations such as OCHA or WHO for Senegal), (adding more specific data collected through the mixed epidemiological survey). This survey was conducted in Senegal in six localities (Dakar, Thies, Diourbel, Kedougou, Saint-Louis and Ziguinchor) chosen according to the number of confirmed cases of COVID-19. In total, 1000 individuals distributed in proportion to the size of the regions were interviewed in April 2021.

Developing forecasting capacity for public health emergency management in Africa using syndemics approach: lessons from the COVID-19 pandemic

“…Furthermore, while a case was made by Morgan and colleagues on the relevance of national forecasting capacities, a strategic action plan for achieving this mandate was not specified. Likewise, our call for forecasting capacity development in Africa is consistent with the submission of Diouf and colleagues, who reported the need to contextualise forecasting models in Africa 11. A vision we believe would be best achieved with local expertise given context effects on results interpretation and decision-making.…”

“…Likewise, our call for forecasting capacity development in Africa is consistent with the submission of Diouf and colleagues, who reported the need to contextualise forecasting models in Africa. 11 A vision we believe would be best achieved with local expertise given context effects on results interpretation and decision-making. Equally, the WHO Regional Office for Africa (WHO AFRO)’s commitment to guarantee health security in Africa through its emergency response flagship programmes that were launched in early 2022 further supports our opinion as well.…”