Abstract
Monkeypox (mpox) is a rare viral disease that can cause severe illness in humans, with outbreaks occurring primarily in central and western Africa. Well-coordinated and synchronized efforts are necessary to understand the factors involved in disease transmission and develop effective health interventions. The aim of this study is to assess the relationship between climate factors and daily mpox cases, as well as to identify the most suitable predictive model for transmission. We analyzed confirmed mpox cases from May 5, 2022, to February 14, 2023, in the 33 most affected countries. We employed and compared the efficiency of four models: Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial. We found a significant correlation between climate factors and daily mpox cases across most of the studied countries. Specifically, for each 1°C increase in the heat index (HI), daily cases increased by 7.7 % (IRR = 1.077, p < 0.05). Conversely, higher relative humidity (RH) decreased daily cases by 2.4 %, and increased wind speed (WS) reduced them by 7.3 %. The HI positively influences mpox spread, while RH and WS act as protective factors. Public health officials should consider these climate influences when developing targeted interventions.
| Original language | English (UK) |
|---|---|
| Article number | 115076 |
| Journal | Journal of Virological Methods |
| Volume | 332 |
| DOIs | |
| Publication status | Published - Feb 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Climate Factors
- Generalized Mixed Models
- Global outbreak analysis
- Heat Index
- Monkeypox
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