Global Chikungunya Virus Risk Projections Under Climate Change Scenarios, 2021-2100

Global land area risk projections for Chikungunya virus (CHIKV) under 16 future climate scenarios. The dataset was created by Qianqian Zhang using ensemble species distribution models for the Aedes aegypti and Aedes albopictus mosquito vectors and the virus itself, with results published on figshare in 2026. It currently identifies 21.26% of global land area across 139 countries as at risk, with projections extending to the year 2100.

Use Cases

• Projecting future disease hotspots based on climate-driven vector suitability.
• Identifying high-priority surveillance zones in temperate regions based on northward expansion projections.
• Assessing region-specific invasion risks based on multi-model ensemble outputs.
• Informing targeted vector control strategies based on identified at-risk countries.

Strengths

• Model performance metrics are provided (e.g., CHIKV model AUC = 0.909, TSS = 0.659).
• Integrates projections for two mosquito vectors and the virus under 16 CMIP6 climate scenarios.
• Explicitly quantifies current global risk at 21.26% of land area across 139 countries.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect modeling bias inherent to the specific ensemble approach and input variables.

Provenance

Source

Qianqian Zhang via figshare

Collection Method

Hierarchical ensemble species distribution modeling using the Biomod2 platform with 19 bioclimatic variables and elevation.

Time Range

Projections from 2021 to 2100.

Freshness

Last updated 2026-05-27 05:07:00; freshness should be verified.

Geography

Global