Exploring the drivers of Crimean-Congo haemorrhagic fever in southern Iraq
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Objectives
Crimean-Congo Haemorrhagic Fever (CCHF) is a zoonotic viral tick-borne disease, which has seen a resurgence in Iraq in recent years, and this study aimed to explore environmental and socioeconomic drivers of this resurgence in southeastern Iraq.
Methods
We used weekly CCHF case data by province and demographic strata (sex, children, adults, older adults) and performed initial covariate exploration using Pearson correlation and penalised feature screening (LASSO, Elastic Net). We fitted generalised additive mixed models (GAMs; negative binomial) with cyclic seasonality and region‑level random effects to a subset of the best performing covariates. Residual temporal autocorrelation was assessed and AR(1) mixed‑effects refits were attempted until a best-fit model was identified.
Results
As anticipated, land-use and many socioeconomic covariates showed strong correlations in initial covariate exploration, and similar patterns were observed among humidity, temperature and precipitation. The main model (total cases) explained ~80% deviance, showing strong seasonality and spatial heterogeneity. The self‑calibrated Palmer Drought Severity Index and counts of incoming internally displaced persons were the most stable predictors.
Conclusions
In southeastern Iraq, CCHF risk was seasonal and spatially heterogeneous and environmental and socioeconomic contexts likely modulate outbreaks and resurgence.
Crimean-Congo Haemorrhagic Fever (CCHF) is a zoonotic viral tick-borne disease, which has seen a resurgence in Iraq in recent years, and this study aimed to explore environmental and socioeconomic drivers of this resurgence in southeastern Iraq.
Methods
We used weekly CCHF case data by province and demographic strata (sex, children, adults, older adults) and performed initial covariate exploration using Pearson correlation and penalised feature screening (LASSO, Elastic Net). We fitted generalised additive mixed models (GAMs; negative binomial) with cyclic seasonality and region‑level random effects to a subset of the best performing covariates. Residual temporal autocorrelation was assessed and AR(1) mixed‑effects refits were attempted until a best-fit model was identified.
Results
As anticipated, land-use and many socioeconomic covariates showed strong correlations in initial covariate exploration, and similar patterns were observed among humidity, temperature and precipitation. The main model (total cases) explained ~80% deviance, showing strong seasonality and spatial heterogeneity. The self‑calibrated Palmer Drought Severity Index and counts of incoming internally displaced persons were the most stable predictors.
Conclusions
In southeastern Iraq, CCHF risk was seasonal and spatially heterogeneous and environmental and socioeconomic contexts likely modulate outbreaks and resurgence.
Date Issued
2026-06-01
Date Acceptance
2026-04-07
Citation
IJID One Health, 2026, 11
ISSN
2949-9151
Publisher
Elsevier
Journal / Book Title
IJID One Health
Volume
11
Copyright Statement
© 2026 The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Publication Status
Published
Article Number
100126
Date Publish Online
2026-04-10