Atividades da AMMnet

This presentation, titled “Preliminary Analysis of the Impact of the Introduction of the Malaria Vaccine on the Incidence of Severe Malaria Among Children Under 5,” examines the epidemiological situation in the health districts of Edéa, Japoma, and Mbanga in Cameroon between 2020 and 2024. Malaria remains a major endemic disease in Cameroon, particularly affecting young children and pregnant women, which led to the inclusion of the malaria vaccine (MV) in the Expanded Program on Immunization in 2024. The study is based on a retrospective analysis of surveillance data and assesses the correlation between third-dose vaccination coverage and trends in severe malaria cases to determine the initial effectiveness of this public health intervention. The results highlight a persistent challenge with a high number of severe malaria cases, as well as a significant decline in vaccination coverage between the first and third doses across all districts studied. However, the analysis reveals a strong negative correlation (r = -0.86) between full vaccination coverage and the increase in severe cases in 2024 compared to 2023. This suggests that, although the overall incidence remains a concern, higher vaccination coverage helps limit the increase in severe forms of the disease. The study therefore underscores the importance of strengthening adherence to the full vaccination schedule to maximize the vaccine’s protective impact in infants.

Join us for the next AMMnet Hackathon, a two-hour, hands-on learning session where you will learn how to build, simulate, and infer epidemiological models using Python, Google Colab, and ChatGPT. No prior experience with epidemiological modeling is required. All experience levels are welcome! By the end of this hackathon, you will be able to: -Understand the SIR (Susceptible–Infected–Recovered) epidemic model -Simulate disease outbreaks using ordinary differential equations (ODEs) -Estimate key epidemiological parameters such as: Transmission rate (β), Recovery rate (γ) & Basic reproduction number (R₀) -Fit models to real outbreak data using: Least squares, Poisson likelihood -Use ChatGPT effectively for: Writing scientific Python code, Debugging models, Explaining results & Generating clean reports All work is done in Google Colab — no local installation required.

A Reunião Anual da AMMNet de 2025 em Dakar, realizada de 25 a 27 de junho, foi um grande sucesso!

A reunião da AMMNet de 2024 foi realizada em Kigali, Ruanda, de 18 a 19 de abril.