Table 1.
Analysis of selected published peer-reviewed studies.
| Study | Quality | Study Location | Study Design | Time Period | Human Cases (n) |
Climatic Factors | Outcome | Co-Factors | Statistical Methods | Results |
|---|---|---|---|---|---|---|---|---|---|---|
| Donalisio (2008) | + | Brazil | Ecological | 1993–2005 | 80 | Rainfall (mm) | HPS cases | Spatial analysis | None | Higher HPS incidence observed in drier months and increased access to food sources by rodents (Harvesting and grain storage and sugar cane cultivation). |
| Donalisio (2011) | ++ | ENM | 1993–2008 | 288 | Winter precipitation | HPS cases | GIS, topography, men > 14 years old and EVI | None | Winter precipitation increased in the dry season and EVI was associated with HPS disease incidence. | |
| Prist (2016) | ++ | Bayesian model | 1993–2012 | 207 | Rainfall and temperature | HCPS risk | HDI, men > 14 years old, sugarcane, population at risk and landscape | t-test, one-way ANOVA, and Tukey’s MCT | HDI and sugarcane cultivation were associated with HCPS cases in the Cerrado whilst males > 14 years old, HDI, sugarcane cultivation and temperature were associated with HPS cases in the Atlantic Forest. | |
| Prist (2017) | + | Bayesian model | 2000–2010 | ? | Temperature, precipitation, RCP4.5 and RCP8.5 | HCPS risk & HCPS cases |
Sugarcane cultivation | Moran’s I, Queen’s case neighbourhood relation | A positive association was observed with increased temperatures & sugarcane cultivation and HCPS risk and HCPS cases. | |
| Muyalert (2019) | ++ | Zero inflated model and temporal term (rw2) + Besag Intrinsic Conditional Auto-Regressive (ICAR) spatial model | 1993–2016 | 1758 | Temperature and precipitation | HCPS risk & HCPS cases |
Host diversity, social vulnerability, and land use change (sugarcane) | INLA | A positive effect was observed with size of population at risk, social vulnerability, rainfall, host diversity, rural workers, land use (sugarcane, maize, and forest cover) on HCPS risk and HCPS cases whilst a negative effect was observed with temperature. | |
| Andreo (2014) | ++ | Argentina | GLM and MaxEnt models | 1995–2009 | 149 | Climate and precipitation related factors | HPS cases | Altitude, rodent host, vegetation, & GIS | Kruskal-Wallis and pairwise Pearson correlation | A positive association of precipitation, forested and scrubland habitats with HPS cases was observed. |
| Vadell (2019) | ++ | GLM | 2004–2015 | 60 | Rainfall and temperature | HPS cases | Area distance from roads, vegetation, topography, number of human inhabitants and reservoir host population | Kappa index, VIF analysis, bootstrap procedure, and residual plots | A positive association with of HPS cases with areas with high percentage of tree cover and locations near rivers was observed. No association with annual precipitation and mean annual temperature was observed and human hantavirus cases. | |
| Ferro (2020) | ++ | Argentina | ARIMA & dynamic regression models | 1997–2017 | 902 | Rainfall and temperature | HPS cases | None | Augmented Dickey-Fuller Test, AICc, RMSE & Ljund-Box test | A positive association of HPS cases with rainfall and temperature was observed with notable delay or lags ranging from two to six months. |
| Montgomery (2012) | - | Bolivia | Epidemiology | 2002 | 45 | Rainfall | HPS cases | Age and farming | None mentioned | A possible association of HPS cases with monthly precipitation levels exists. |
| Nsoesie (2014) | ++ | Chile | ARIMA and regression with ARIMA errors | 2001–2012 | 667 | Precipitation, temperature & humidity | HPS cases | None | R2 and RMSE | Positive associations of HPS cases with peaks in temperatures and HPS troughs with precipitation and humidity levels were observed. |
| Bayard (2004) | − | Panama | Outbreak investigation | 1999–2000 | 9 | Precipitation | HPS cases | None | None mentioned | A positive association of HPS cases with increased rainfall (two to threefold) during September/October 1999 (outbreak year) was observed. |
| Williams (1997) | − | Paraguay | Outbreak investigation | 1995–1996 | 17 | Precipitation | HPS cases | None | None mentioned | A positive association of HPS cases with increased rainfall (10-fold) during the 1995 (outbreak year) was observed. |
| Douglas (2021) | + | Barbados | Cross-sectional epidemiology | 2008–2016 | 862 | Rainfall (seasonality) | Hantavirus cases * | Gender, age and urban location | 95% CI | A positive association of human hantavirus infections with rainy season, age, gender, and geospatial location was observed. |
Key ?—not specified; ++ very high quality study; + high quality study; − low quality study; *—hantavirus cases refer to laboratory confirmed hantavirus infect ions via ELISA testing not via syndromic surveillance (the strain(s) involved is/are currently unknown); Akaike information criteria (AICc); Analysis of variance (ANOVA); Autoregressive Integrated Moving Average (ARIMA); confidence intervals (CI); Ecological Niche model (ENM); EVI (Enhanced Vegetation Index); geographical information systems (GIS); Generalised linear model (GLM); Human development index (HDI), Hantavirus pulmonary syndrome (HPS); Hantavirus cardiopulmonary syndrome (HCPS); Integrated nested Laplace approximations (INLA); Tukey’s multiple comparison tests (MCT); Representative Concentration Pathway 4.5 (RCP4.5), Representative Concentration Pathway 8.5 (RCP 8.5); Root mean square error (RMSE); Variance inflation factor (VIF); Coefficient of variation R2.