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Using advanced data analytics for more informed COVID-19 vaccination decision making in Malawi

While the burden of COVID-19 cases and deaths in Africa has gone down due to the implementation of public health measures (including vaccination), COVID-19 vaccine coverage on the continent still falls below the 70 percent target recommended by the World Health Organization and the African Union. And in Malawi and Madagascar specifically, COVID-19 vaccination coverage was approximately 30 percent and 13 percent respectively as of 2023—in comparison to the more than 60 percent average of the population in developed countries.

So in 2023, CHISU initiated a multi-site research study to assess the health impact (cases and deaths averted), economic impact, and cost-effectiveness of COVID-19 vaccination in Malawi and Madagascar using combined statistical, epidemiological, and economic models. 

The study generated estimates for predicted number of cases, deaths, and hospitalization indicators over a one-year period under different vaccine coverage scenarios. CHISU explored whether the decline or increase in transmission of the virus was associated with vaccination coverage, controlling for the confounding effect of nonpharmaceutical interventions (such as school closures, workplace closures, cancellation of public events, limits on gathering size, closure of public transport, and stay-at-home requirements).

 

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The study also highlights the role of mathematical models in policy analysis and utility in decision making. It found vaccination contributed to reducing the burden of COVID-19 by reducing transmission intensity of the virus, reducing daily incidence cases, and reducing COVID-19-induced deaths among the population.

Validating mathematical models ensures that the data is accurate and reliable. In January 2024, CHISU facilitated the first data validation workshop in Lilongwe, Malawi with three objectives:

  1. Present initial research findings 
  2. Gain consensus from the local government on data points used to parametrize the initial models 
  3. Build local capacity for economic modeling

More than 20 participants including health economists, health financers, data managers, and representatives from Malawi’s Department of Health Policy attended the three-day workshop. Participants were able to provide feedback on the feasibility of the initial model outputs, make recommendations on additional data sources, and provide missing local data to strengthen the contextual relevance of the models.

The workshop also contained a capacity-building component, which aimed to ensure Malawi will have the local expertise to plan resources for future pandemics using similar modeling techniques.

One of the primary challenges identified during the data validation process was the lack of adequate vaccine costing data for Malawi. Consequently, data from other countries were used to put parameters on the economic model. Mathematical models rely on substantial data, so it’s common practice to supplement data that may be incomplete or unavailable.

However, Malawi’s Ministry of Health disagreed with this approach and committed to identifying relevant local vaccine costing data. The initial models will subsequently be revised with local data sources to ensure model outputs have a stronger relevance to the Malawian context. A similar data validation workshop will also be held by CHISU in Madagascar.

The CHISU research team also met with the Secretary for Health, the Director of Health Policy, and the Chief of Health Services. CHISU’s Resident Advisor for Malawi Jacob Kawonga was able to provide details on the overall activities being supported in Malawi. 

“While COVID-19 was no longer an emergency, capacity building within the Ministry of Health—including building local expertise in mathematical modeling—was necessary for the country’s response to future pandemics," said Dr. Samson Mndolo, Secretary for Health.

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