Spatio-temporal agent-based modelling of malaria
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arXiv
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| Autores principales: | , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866912386934374400 |
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| author | Walker, Camelia R. Anwar, Md Nurul Brauninger, Leandra Richards, Jack Ataide, Ricardo Thang, Ngo Duc Thang, Nguyen Xuan Canavati, Sara Flegg, Jennifer A. |
| author_facet | Walker, Camelia R. Anwar, Md Nurul Brauninger, Leandra Richards, Jack Ataide, Ricardo Thang, Ngo Duc Thang, Nguyen Xuan Canavati, Sara Flegg, Jennifer A. |
| contents | Plasmodium falciparum is responsible for the majority of malaria morbidity and mortality each year. Malaria transmission rates vary by location and time of year due to climate and environmental conditions. We show the impact of these factors by developing a stochastic spatiotemporal agent-based malaria model that captures the impact of spatially distributed interventions on malaria transmission. Our model uses spatiotemporal estimates of mosquito climatic suitability and household location data to model the interaction between human and mosquito agents. We apply our model to investigate how strategies for distributing interventions to households in Vietnam impact the disease burden. Our study shows that providing some level of protection to a wide range of households reduces malaria prevalence more compared to providing a strong level of protection to a limited number of households. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_16240 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Spatio-temporal agent-based modelling of malaria Walker, Camelia R. Anwar, Md Nurul Brauninger, Leandra Richards, Jack Ataide, Ricardo Thang, Ngo Duc Thang, Nguyen Xuan Canavati, Sara Flegg, Jennifer A. Populations and Evolution Plasmodium falciparum is responsible for the majority of malaria morbidity and mortality each year. Malaria transmission rates vary by location and time of year due to climate and environmental conditions. We show the impact of these factors by developing a stochastic spatiotemporal agent-based malaria model that captures the impact of spatially distributed interventions on malaria transmission. Our model uses spatiotemporal estimates of mosquito climatic suitability and household location data to model the interaction between human and mosquito agents. We apply our model to investigate how strategies for distributing interventions to households in Vietnam impact the disease burden. Our study shows that providing some level of protection to a wide range of households reduces malaria prevalence more compared to providing a strong level of protection to a limited number of households. |
| title | Spatio-temporal agent-based modelling of malaria |
| topic | Populations and Evolution |
| url | https://arxiv.org/abs/2505.16240 |