Large-scale Epidemiological modeling: Scanning for Mosquito-Borne Diseases Spatio-temporal Patterns in Brazil
The influence of climate on mosquito-borne diseases like dengue and chikungunya is well-established, but comprehensively tracking long-term spatial and temporal trends across large areas has been hindered by fragmented data and limited analysis tools. This study presents an unprecedented analysis, i...
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Main Authors: | , , , , , , , , , , |
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Format: | Journal Article |
Language: | English |
Published: |
30-07-2024
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Subjects: | |
Online Access: | Get full text |
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Summary: | The influence of climate on mosquito-borne diseases like dengue and
chikungunya is well-established, but comprehensively tracking long-term spatial
and temporal trends across large areas has been hindered by fragmented data and
limited analysis tools. This study presents an unprecedented analysis, in terms
of breadth, estimating the SIR transmission parameters from incidence data in
all 5,570 municipalities in Brazil over 14 years (2010-2023) for both dengue
and chikungunya. We describe the Episcanner computational pipeline, developed
to estimate these parameters, producing a reusable dataset describing all
dengue and chikungunya epidemics that have taken place in this period, in
Brazil. The analysis reveals new insights into the climate-epidemic nexus: We
identify distinct geographical and temporal patterns of arbovirus disease
incidence across Brazil, highlighting how climatic factors like temperature and
precipitation influence the timing and intensity of dengue and chikungunya
epidemics. The innovative Episcanner tool empowers researchers and public
health officials to explore these patterns in detail, facilitating targeted
interventions and risk assessments. This research offers a new perspective on
the long-term dynamics of climate-driven mosquito-borne diseases and their
geographical specificities linked to the effects of global temperature
fluctuations such as those captured by the ENSO index. |
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DOI: | 10.48550/arxiv.2407.21286 |