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

Environ Res

Mahidol Oxford Tropical Medicine Research Unit (MORU), Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK; The Open University, Milton Keynes, UK.

Published: December 2024

AI Article Synopsis

  • Scrub typhus is increasingly recognized as a global public health issue, yet it remains underdiagnosed and underreported, prompting a systematic review to explore environmental factors affecting its occurrence and prediction methods.
  • The review analyzed 68 studies from multiple databases, highlighting key environmental risk factors like temperature, precipitation, humidity, sunshine duration, elevation, vegetation index, and cropland, while noting a lack of exploration into socioeconomic and biological factors.
  • Common predictive methods identified include Autoregressive Integrated Moving Average (ARIMA) for temporal trends and ecological niche modeling (ENM) for spatial distribution, with the study calling attention to knowledge gaps and recommending further research in disease prediction and burden analysis.

Article Abstract

Background: Scrub 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.

Methods: In 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.

Results: We 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.

Conclusions: Our 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 Registration: PROSPERO CRD42022315209.

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Source
http://dx.doi.org/10.1016/j.envres.2024.120067DOI Listing

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