The influence of climate variation and change on diarrheal disease in the Pacific Islands

Spatial heterogeneity of bacillary dysentery and the impact of temperature in the Beijing-Tianjin-Hebei region of China

Previous studies indicate that the incidence of bacillary dysentery is closely related to meteorological factors. However, the impact of temperature and the spatial heterogeneity of the disease in regions of unbalanced socioeconomic development remains unclear. Therefore, this research collected data for 29,639 daily bacillary dysentery cases in children under 5 years of age, as well as the meteorological variables from China's Beijing-Tianjin-Hebei region, to analyze the spatial pattern of bacillary dysentery and reveal its nonlinear association with temperature. The SatScan method was employed first, to detect the spatial heterogeneity of the disease risk, and then the distributed lag nonlinear model (DLNM) was used to analyze the relationships between the daily minimum, mean, and maximum temperatures and bacillary dysentery in the stratified heterogeneous regions. The results indicated that bacillary dysentery incidence presented statistically significant spatial heterogeneity. The area of highest risk was found to be Beijing and its neighboring regions, which have high population densities. There was also a positive association between bacillary dysentery and temperature. Hotter temperatures were accompanied by higher relative risks. In the most likely spatial cluster region, the excess risk (ER) values for a 1°C rise in minimum, mean, and maximum temperatures above the median were 4.65%, 11.30%, and 19.21%, respectively. The effect of temperature on bacillary dysentery peaked at a lag of 3 to 4 days. The findings of this study will aid risk assessments and early warning systems for bacillary dysentery.

Rainfall variation and child health: effect of rainfall on diarrhea among under 5 children in Rwanda, 2010

Background

Diarrhea among children under 5 years of age has long been a major public health concern. Previous studies have suggested an association between rainfall and diarrhea. Here, we examined the association between Rwandan rainfall patterns and childhood diarrhea and the impact of household sanitation variables on this relationship.

Methods

We derived a series of rain-related variables in Rwanda based on daily rainfall measurements and hydrological models built from daily precipitation measurements collected between 2009 and 2011. Using these data and the 2010 Rwanda Demographic and Health Survey database, we measured the association between total monthly rainfall, monthly rainfall intensity, runoff water and anomalous rainfall and the occurrence of diarrhea in children under 5 years of age.

Results

Among the 8601 children under 5 years of age included in the survey, 13.2 % reported having diarrhea within the 2 weeks prior to the survey. We found that higher levels of runoff were protective against diarrhea compared to low levels among children who lived in households with unimproved toilet facilities (OR = 0.54, 95 % CI: [0.34, 0.87] for moderate runoff and OR = 0.50, 95 % CI: [0.29, 0.86] for high runoff) but had no impact among children in household with improved toilets.

Conclusion

Our finding that children in households with unimproved toilets were less likely to report diarrhea during periods of high runoff highlights the vulnerabilities of those living without adequate sanitation to the negative health impacts of environmental events.

Climatic Drivers of Diarrheagenic Escherichia coli Incidence: A Systematic Review and Meta-analysis

BACKGROUND

Positive associations have been noted between temperature and diarrhea incidence, but considerable uncertainty surrounds quantitative estimates of this relationship because of pathogen-specific factors and a scarcity of data on the influence of meteorological factors on the risk of disease. Quantifying these relationships is important for disease prevention and climate change adaptation.

METHODS

To address these issues, we performed a systematic literature review of studies in which at least 1 full year of data on the monthly incidence of diarrheagenic Escherichia coli were reported. We characterized seasonal patterns of disease incidence from 28 studies. In addition, using monthly time- and location-specific weather data for 18 studies, we performed univariate Poisson models on individual studies and a meta-analysis, using a generalized estimating equation, on the entire data set.

RESULTS

We found an 8% increase in the incidence of diarrheagenic E. coli (95% confidence interval, 5%-11%; P < .0001) for each 1°C increase in mean monthly temperature. We found a modest positive association between 1-month-lagged mean rainfall and incidence of diarrheagenic E. coli, which was not statistically significant when we controlled for temperature.

CONCLUSIONS

These results suggest that increases in ambient temperature correspond to an elevated incidence of diarrheagenic E. coli and underscore the need to redouble efforts to prevent the transmission of these pathogens in the face of increasing global temperatures.

A systematic review and meta-analysis of ambient temperature and diarrhoeal diseases

BACKGROUND

Global climate change is expected to increase the risk of diarrhoeal diseases, a leading cause of childhood mortality. However, there is considerable uncertainty about the magnitude of these effects and which populations bear the greatest risks.

METHODS

We conducted a systematic review using defined search terms across four major databases and, additionally, examined the references of 54 review articles captured by the search. We evaluated sources of heterogeneity by pathogen taxon, exposure measure, study quality, country income level and regional climate, and estimated pooled effect estimates for the subgroups identified in the heterogeneity analysis, using meta-analysis methods.

RESULTS

We identified 26 studies with 49 estimates. Pathogen taxa were a source of heterogeneity. There was a positive association between ambient temperature and all-cause diarrhoea (incidence rate ratio (IRR) 1.07; 95% confidence interval (CI) 1.03, 1.10) and bacterial diarrhoea (IRR 1.07; 95% CI 1.04, 1.10), but not viral diarrhoea (IRR 0.96; 95% CI 0.82, 1.11). These associations were observed in low-, middle- and high-income countries. Only one study of protozoan diarrhoea was identified.

CONCLUSIONS

Changes in temperature due to global climate change can and may already be affecting diarrhoeal disease incidence. The vulnerability of populations may depend, in part, on local pathogen distribution. However, evidence of publication bias and the uneven geographical distribution of studies limit the precision and generalizability of the pooled estimates.

High temperature as a risk factor for infectious diarrhea in Shanghai, China

BACKGROUND

Recent studies indicate that ambient temperature could be a risk factor for infectious diarrhea, but evidence for such a relation is limited in China.

METHODS

We investigated the short-term association between daily temperature and physician-diagnosed infectious diarrhea during 2008-2010 in Shanghai, China. We adopted a time-series approach to analyze the data and a quasi-Poisson regression model with a natural spline-smoothing function to adjust for long-term and seasonal trends, as well as other time-varying covariates.

RESULTS

There was a significant association between temperature and outpatient visits for diarrhea. A 1°C increase in the 6-day moving average of temperature was associated with a 2.68% (95% CI: 1.83%, 3.52%) increase in outpatient visits for diarrhea. We did not find a significant association between rainfall and infectious diarrhea.

CONCLUSIONS

High temperature might be a risk factor for infectious diarrhea in Shanghai. Public health programs should focus on preventing diarrhea related to high temperature among city residents.

Health impact assessment of global climate change: expanding on comparative risk assessment approaches for policy making

Climate change is projected to have adverse impacts on public health. Cobenefits may be possible from more upstream mitigation of greenhouse gases causing climate change. To help measure such cobenefits alongside averted disease-specific risks, a health impact assessment (HIA) framework can more comprehensively serve as a decision support tool. HIA also considers health equity, clearly part of the climate change problem. New choices for energy must be made carefully considering such effects as additional pressure on the world's forests through large-scale expansion of soybean and oil palm plantations, leading to forest clearing, biodiversity loss and disease emergence, expulsion of subsistence farmers, and potential increases in food prices and emissions of carbon dioxide to the atmosphere. Investigators must consider the full range of policy options, supported by more comprehensive, flexible, and transparent assessment methods.

Association between climate variability and hospital visits for non-cholera diarrhoea in Bangladesh: effects and vulnerable groups

BACKGROUND

We estimated the effects of rainfall and temperature on the number of non-cholera diarrhoea cases and identified population factors potentially affecting vulnerability to the effect of the climate factors in Dhaka, Bangladesh.

METHODS

Weekly rainfall, temperature and number of hospital visits for non-cholera diarrhoea were analysed by time-series regression. A Poisson regression model was used to model the relationships controlling for seasonally varying factors other than the weather variables. Modifications of weather effects were investigated by fitting the models separately to incidence series according to their characteristics (sex, age, socio-economic, hygiene and sanitation status).

RESULTS

The number of non-cholera diarrhoea cases per week increased by 5.1% (95% CI: 3.3-6.8) for every 10 mm increase above the threshold of 52 mm of average rainfall over lags 0-8 weeks. The number of cases also increased by 3.9% (95% CI: 0.6-7.2) for every 10 mm decrease below the same threshold of rainfall. Ambient temperature was also positively associated with the number of non-cholera diarrhoea cases. There was no evidence for the modification of both 'high and low rainfall' effects by individual characteristics, while the effect of temperature was higher amongst those individuals at a lower educational attainment and unsanitary toilet users.

CONCLUSIONS

The number of non-cholera diarrhoea cases increased both above and below a threshold level with high and low rainfall in the preceding weeks. The number of cases also increased with higher temperature, particularly in those individuals at a lower socio-economic and sanitation status.

Healthy people 2100: modeling population health impacts of climate change

Quantitatively estimating the potential health impacts of climate change is facilitated by multi-determinant models that integrate micro- to macro-level exposures and processes that influence disease occurrence, including the public health responses, in order to identify regions and population groups that may be more vulnerable. Although progress has been made in constructing systems-based models, considerable work is required to address key issues of quantification of the climate-health associations and the factors that affect those associations; specification of model(s) appropriate to incorporate climate change, adaptation, and mitigation policies; incorporation of thresholds; incorporation of pathways of public health development; and quantification of uncertainties.