Abstract / Summary
Malaria remains a major mosquito-borne infectious disease, transmitted primarily by female Anopheles mosquitoes, with its transmission strongly influenced by environmental conditions. This systematic review synthesizes the existing evidence on the relationship between environmental factors and malaria transmission. It identifies the environmental determinants most frequently investigated, evaluates the direction and consistency of their associations with malaria outcomes, and summarizes the analytical methods used in previous studies. The included studies retrieved data from major bibliographic databases, including Web of Science, PubMed, and Scopus, to investigate the relationship between environmental factors and malaria transmission. A total of 53 studies met the eligibility criteria and were included in this systematic review. The most frequently examined environmental variables were temperature, precipitation, humidity, wind speed, air pressure, air pollution, and sky clarity. Regression- and correlation-based analyses were the predominant statistical approaches used to assess the associations between these environmental factors and malaria transmission. Most studies reported positive associations between temperature, humidity, and malaria transmission. The minimum temperature thresholds for Plasmodium falciparum (~ 18 °C) and Plasmodium vivax (~ 15 °C) were found to be crucial for transmission. Mosquito survival was shown to be enhanced by humidity levels above 60%, although breeding was aided by precipitation, particularly in dry environments. However, several studies found negative or non-significant relationships between malaria and environmental conditions, demonstrating variation among locations and study methods. This review shows that environmental determinants, notably temperature, humidity, and precipitation, have a major influence on malaria transmission, while their effects vary depending on the situation. These findings highlight the importance of incorporating environmental determinants into malaria surveillance and prediction models to improve early warning systems and support evidence-based malaria control strategies.