Publications by authors named "Monique Ambrose"
Background: For their 2021-2025 National Malaria Strategic Plan (NMSP), Nigeria's National Malaria Elimination Programme (NMEP), in partnership with the World Health Organization (WHO), developed a targeted approach to intervention deployment at the local government area (LGA) level as part of the High Burden to High Impact response. Mathematical models of malaria transmission were used to predict the impact of proposed intervention strategies on malaria burden.
Methods: An agent-based model of Plasmodium falciparum transmission was used to simulate malaria morbidity and mortality in Nigeria's 774 LGAs under four possible intervention strategies from 2020 to 2030.
Article Synopsis
- WHO recommends adapting perennial malaria chemoprevention (PMC) timing and doses based on local conditions, but knowledge gaps about its effects and combining it with the RTS,S malaria vaccine complicate decision-making in high-burden countries.
- The EMOD malaria model was used to simulate the impact of PMC and RTS,S on malaria cases in children under two, with findings indicating that both interventions are most effective at moderate to high transmission levels and show improved outcomes when used together.
- The study concludes that PMC could significantly reduce both clinical and severe malaria cases, especially when combined with RTS,S and with adequate coverage, suggesting a need for tailored implementation strategies based on local epidemiology.
Article Synopsis
- In malaria-affected countries, it's essential to focus intervention efforts on the areas that need it most for effective progress.
- Global and national decision-makers use epidemiological data and mathematical models to guide health initiatives, relying heavily on data from the Demographic and Health Surveys (DHS) Program to understand local malaria prevalence and intervention coverage.
- The text highlights limitations in current survey designs, particularly in Nigeria, and suggests enhancements to survey questions and sampling strategies that could improve data quality, necessitating collaboration among various stakeholders to tackle these data challenges.
Two zoonotic influenza A viruses (IAV) of global concern, H5N1 and H7N9, exhibit unexplained differences in age distribution of human cases. Using data from all known human cases of these viruses, we show that an individual's first IAV infection confers lifelong protection against severe disease from novel hemagglutinin (HA) subtypes in the same phylogenetic group. Statistical modeling shows that protective HA imprinting is the crucial explanatory factor, and it provides 75% protection against severe infection and 80% protection against death for both H5N1 and H7N9.
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