A systematic review of environmental covariates and methods for spatial or temporal scrub typhus distribution prediction

Abstract

BackgroundScrub typhus is underdiagnosed and underreported but emerging as a global public health problem. To inform future burden and prediction studies we examined through a systematic review the potential effect of environmental covariates on scrub typhus occurrence and the methods which have been used for its prediction. MethodsIn this systematic review, we searched PubMed, Scopus, Web of Science, China National Knowledge Infrastructure and other databases, with no language and publication time restrictions, for studies that investigated environmental covariates or utilized methods to predict the spatial or temporal human. Data were manually extracted following a set of queries and systematic analysis was conducted. ResultsWe included 68 articles published in 1978–2024 with relevant data from 7 countries/regions. Significant environmental risk factors for scrub typhus include temperature (showing positive or inverted-U relationships), precipitation (with positive or inverted-U patterns), humidity (exhibiting complex positive, inverted-U, or W-shaped associations), sunshine duration (with positive, inverted-U associations), elevation, the normalized difference vegetation index (NDVI), and the proportion of cropland. Socioeconomic and biological factors were rarely explored. Autoregressive Integrated Moving Average (ARIMA) (n = 8) and ecological niche modelling (ENM) approach (n = 11) were the most popular methods for predicting temporal trends and spatial distribution of scrub typhus, respectively. ConclusionsOur findings summarized the evidence on environmental covariates affecting scrub typhus occurrence and the methodologies used for predictive modelling. We review the existing knowledge gaps and outline recommendations for future studies modelling disease prediction and burden. Trial registrationPROSPERO CRD42022315209.