Challenges in developing methods for quantifying the effects of weather and climate on water-associated diseases: A systematic review

Abstract

Infectious diseases attributable to unsafe water supply, sanitation and hygiene (e.g. Cholera, Leptospirosis, Giardiasis) remain an important cause of morbidity and mortality, especially in low-income countries. Climate and weather factors are known to affect the transmission and distribution of infectious diseases and statistical and mathematical modelling are continuously developing to investigate the impact of weather and climate on water-associated diseases. There have been little critical analyses of the methodological approaches. Our objective is to review and summarize statistical and modelling methods used to investigate the effects of weather and climate on infectious diseases associated with water, in order to identify limitations and knowledge gaps in developing of new methods. We conducted a systematic review of English-language papers published from 2000 to 2015. Search terms included concepts related to water-associated diseases, weather and climate, statistical, epidemiological and modelling methods. We found 102 full text papers that met our criteria and were included in the analysis. The most commonly used methods were grouped in two clusters: process-based models (PBM) and time series and spatial epidemiology (TS-SE). In general, PBM methods were employed when the bio-physical mechanism of the pathogen under study was relatively well known (e.g. Vibrio cholerae); TS-SE tended to be used when the specific environmental mechanisms were unclear (e.g. Campylobacter). Important data and methodological challenges emerged, with implications for surveillance and control of water-associated infections. The most common limitations comprised: non-inclusion of key factors (e.g. biological mechanism, demographic heterogeneity, human behavior), reporting bias, poor data quality, and collinearity in exposures. Furthermore, the methods often did not distinguish among the multiple sources of time-lags (e.g. patient physiology, reporting bias, healthcare access) between environmental drivers/exposures and disease detection. Key areas of future research include: disentangling the complex effects of weather/climate on each exposure-health outcome pathway (e.g. person-to-person vs environment-to-person), and linking weather data to individual cases longitudinally.

Fig 1. Illustration of the steps and potential pathways from being exposed to the pathogen reservoir to detection of disease.

The red (blue) taps and swimmers represent contaminated (uncontaminated) drinking and recreational water. The red (blue) silhouette represents infected (not-infected) humans. Here and throughout, any kind of environment-containing pathogens that can serve as a medium for transmission (e.g. drinking water, sewage system) is referred to as “pathogen reservoir”; any form of direct or indirect contact with such medium, irrespective of the presence of the pathogen, is referred to as an “exposure”. According to this conceptual scheme, a disease-free situation is the combination of negligible pathogen population in, and/or negligible exposure of susceptible individuals to, the pathogen reservoir. Infections arise from increased interactions of exposed susceptibles with the pathogen reservoir. This can be caused by a growth in the pathogen population (driven, for example, by temperature) and/or larger exposure to the pathogen. An increase in the exposure can be directly or indirectly driven by meteorological/climate variables (e.g. high temperature increasing the risk of drinking contaminated water), environmental causes (e.g. poor water drainage management due to land use), and behavioural and/or socio-economic factors (e.g. recreational activity in unclean water). Changes in the population of susceptibles (for example due to immigration, loss of immunity and/or human-to-human transmission) can alter the patterns of exposure.

Fig 2. Flow chart describing the selection process of all abstracts.

Fig 3. Proportion of papers investigating a particular pathogen or disease.

Fig 4. (a) Distribution of countries for which water-associated disease data were the focus of the reviewed papers (b) Geographic distribution of the 7 most commonly studied water-associated pathogens (resulting either in an epidemic or endemic situations) which were the focus of the reviewed papers.

Each circle refers to specific countries, In particular, the largest circle in Asia, refers to Bangladesh.

Fig 5. Cluster analysis of methods.

Each dot corresponds to a reviewed paper; the brown bubbles correspond to the keywords describing the techniques. A connection between a paper and a keyword occurs when the related technique is used. The size of the bubble increases (logarithmically) with the number of papers citing the keyword. For visual purpose only, i) the bubbles are displayed with different shades of brown and ii) the technical keywords (listed in S1 Table in the Supporting Information) describing methods used by only one paper are not displayed (the full set is shown in S1 Fig in the Supporting Information). The graph was produced by using the i-graph package[13] in R.

Fig 6. The most common, general methods used in the reviewed papers (listed in S1 Table in the supporting information).

Fig 7. The most common environmental and socio-economic variables included in the reviewed papers.