Projected burden of disease for Salmonella infection due to increased temperature in Australian temperate and subtropical regions

Climate change, extreme events, and increased risk of salmonellosis: foodborne diseases active surveillance network (FoodNet), 2004-2014

BACKGROUND

Infections with nontyphoidal Salmonella cause an estimated 19,336 hospitalizations each year in the United States. Sources of infection can vary by state and include animal and plant-based foods, as well as environmental reservoirs. Several studies have recognized the importance of increased ambient temperature and precipitation in the spread and persistence of Salmonella in soil and food. However, the impact of extreme weather events on Salmonella infection rates among the most prevalent serovars, has not been fully evaluated across distinct U.S. regions.

METHODS

To address this knowledge gap, we obtained Salmonella case data for S. Enteriditis, S. Typhimurium, S. Newport, and S. Javiana (2004-2014; n = 32,951) from the Foodborne Diseases Active Surveillance Network (FoodNet), and weather data from the National Climatic Data Center (1960-2014). Extreme heat and precipitation events for the study period (2004-2014) were identified using location and calendar day specific 95^th percentile thresholds derived using a 30-year baseline (1960-1989). Negative binomial generalized estimating equations were used to evaluate the association between exposure to extreme events and salmonellosis rates.

RESULTS

We observed that extreme heat exposure was associated with increased rates of infection with S. Newport in Maryland (Incidence Rate Ratio (IRR): 1.07, 95% Confidence Interval (CI): 1.01, 1.14), and Tennessee (IRR: 1.06, 95% CI: 1.04, 1.09), both FoodNet sites with high densities of animal feeding operations (e.g., broiler chickens and cattle). Extreme precipitation events were also associated with increased rates of S. Javiana infections, by 22% in Connecticut (IRR: 1.22, 95% CI: 1.10, 1.35) and by 5% in Georgia (IRR: 1.05, 95% CI: 1.01, 1.08), respectively. In addition, there was an 11% (IRR: 1.11, 95% CI: 1.04-1.18) increased rate of S. Newport infections in Maryland associated with extreme precipitation events.

CONCLUSIONS

Overall, our study suggests a stronger association between extreme precipitation events, compared to extreme heat, and salmonellosis across multiple U.S. regions. In addition, the rates of infection with Salmonella serovars that persist in environmental or plant-based reservoirs, such as S. Javiana and S. Newport, appear to be of particular significance regarding increased heat and rainfall events.

Comparison of heat-illness associations estimated with different temperature metrics in the Australian Capital Territory, 2006-2016

While the associations of heat with health outcomes is well researched, there is less consensus on the measures used to define heat exposure and the short-term and delayed impacts of different temperature metrics on health outcomes. We investigate the nonlinear and short-term relationship of three temperature metrics and reported incidence of three gastrointestinal illnesses: salmonellosis, campylobacteriosis and cryptosporidiosis in the Australian Capital Territory (ACT). We also examine the nonlinear association of these illnesses with extreme heat (5th, 75th, 90th percentile of all heat measures). Generalized linear models with Poisson regression accounting for overdispersion, seasonal and long-term trend, weekly number of outbreaks and rainfall were developed for mean and maximum weekly temperature and the heat stress index (EHI_accl). Bacterial illnesses (salmonellosis and campylobacteriosis) showed an overall positive association with extreme heat (75th and 90th percentile of all three heat measures) and an inverse association with low temperature (5th percentile). The shape of the exposure-response curve across a range of temperatures and the lagged effects varied for each disease. Modelling the short-term and delayed effects of heat using different metrics across a range of illnesses can help identify the most appropriate measure to inform local public health intervention planning for heat-related emergencies.

Phage therapy as a potential approach in the biocontrol of pathogenic bacteria associated with shellfish consumption

Infectious human diseases acquired from bivalve shellfish consumption constitute a public health threat. These health threats are largely related to the filter-feeding phenomenon, by which bivalve organisms retain and concentrate pathogenic bacteria from their surrounding waters. Even after depuration, bivalve shellfish are still involved in outbreaks caused by pathogenic bacteria, which increases the demand for new and efficient strategies to control transmission of shellfish infection. Bacteriophage (or phage) therapy represents a promising, tailor-made approach to control human pathogens in bivalves, but its success depends on a deep understanding of several factors that include the bacterial communities present in the harvesting waters, the appropriate selection of phage particles, the multiplicity of infection that produces the best bacterial inactivation, chemical and physical factors, the emergence of phage-resistant bacterial mutants and the life cycle of bivalves. This review discusses the need to advance phage therapy research for bivalve decontamination, highlighting their efficiency as an antimicrobial strategy and identifying critical aspects to successfully apply this therapy to control human pathogens associated with bivalve consumption.

Effects of Floods on the Incidence of Acute Hemorrhagic Conjunctivitis in Mengshan, China, from 2005 to 2012

This study aimed to examine the association between floods and the morbidity of acute hemorrhagic conjunctivitis (AHC) in Mengshan, China. Relying on the longitudinal data, a generalized additive model (GAM) was applied to quantify the relationship between the morbidity of AHC and floods from 2005 to 2012, controlling for other meteorological variables. Years lived with disability (YLDs) and attributable YLDs were used as the measure of the burden of AHC because of the floods. Multivariable analysis showed that floods were significantly associated with an increased risk of the morbidity of AHC (rate ratio [RR] = 2.136, 95% CI: 2.109-2.163). The total YLDs per 1,000 in Mengshan was 0.2001, although the value in females was higher than that in males (0.2351 versus 0.1686). The YLD per 1,000 of AHC in Mengshan was highest between the ages of 5 and 14 years (0.6530), followed by the age of 0-4 years (0.3325). The attributable YLD per 1,000 of AHC due to the floods in Mengshan was 0.0434 (95% CI: 0.0425-0.0442). Our study confirms that floods have significantly increased the risks of AHC in the selected study area. Females and youngsters may be the vulnerable populations to develop the flood-related disease.

Impacts of exposure to ambient temperature on burden of disease: a systematic review of epidemiological evidence

Ambient temperature is an important determinant of mortality and morbidity, making it necessary to assess temperature-related burden of disease (BD) for the planning of public health policies and adaptive responses. To systematically review existing epidemiological evidence on temperature-related BD, we searched three databases (PubMed, Web of Science, and Scopus) on 1 September 2018. We identified 97 studies from 56 counties for this review, of which 75 reported the fraction or number of health outcomes (include deaths and diseases) attributable to temperature, and 22 reported disability-adjusted life years (include years of life lost and years lost due to disability) related to temperature. Non-optimum temperatures (i.e., heat and cold) were responsible for > 2.5% of mortality in all included high-income countries/regions, and > 3.0% of mortality in all included middle-income countries. Cold was mostly reported to be the primary source of mortality burden from non-optimum temperatures, but the relative role of three different temperature exposures (i.e., heat, cold, and temperature variability) in affecting morbidity and mortality remains unclear so far. Under the warming climate scenario, almost all projections assuming no population adaptation suggested future increase in heat-related but decrease in cold-related BD. However, some studies emphasized the great uncertainty in future pattern of temperature-related BD, largely depending on the scenarios of climate, population adaptation, and demography. We also identified important discrepancies and limitations in current research methodologies employed to measure temperature exposures and model temperature-health relationship, and calculate the past and project future temperature-related BD. Overall, exposure to non-optimum ambient temperatures has become and will continue to be a considerable contributor to the global and national BD, but future research is still needed to develop a stronger methodological framework for assessing and comparing temperature-related BD across different settings.

Divergent geography of Salmonella Wangata and Salmonella Typhimurium epidemiology in New South Wales, Australia

Salmonella enterica serovar Wangata is an important cause of salmonellosis in the state of New South Wales, Australia. Standard surveillance has not identified a common food source and cases have been attributed to an unknown environmental or wildlife reservoir. Investigation of the spatial distribution of cases may provide valuable insights into local risk factors for infection and the potential role of the environment and wildlife.

Using conditional autoregressive analysis, we explored the association between laboratory-confirmed cases of S. Wangata reported to the New South Wales Department of Health and human socio-demographic, climate, land cover and wildlife features. For comparison, a model was also fitted to investigate the association of cases of Salmonella enterica serovar Typhimurium, an established foodborne serotype, with the same features. To determine if cases of S. Wangata were associated with potential wildlife reservoir species, additional variables were included in the S. Wangata model that indicated areas of high suitability for each species.

We found that cases of S. Wangata were associated with warmer temperatures, proximity to wetlands and amphibian species richness. In contrast, cases of S. Typhimurium were associated with human demographic features (proportion of the population comprising children <5 years old), climate (mean annual precipitation and mean annual temperature) and land cover (proportion comprising urban and evergreen broadleaf forest). These findings support the hypothesis that S. Wangata is likely to be associated with an environmental source. Whilst we expected S. Typhimurium to be associated with the human socio-demographic feature, the significance of the land cover features was surprising and might suggest the epidemiology of S. Typhimurium in Australia is more complex than currently understood.

Projected Changes in Maternal Heat Exposure During Early Pregnancy and the Associated Congenital Heart Defect Burden in the United States

Background More intense and longer-lasting heat events are expected in the United States as a consequence of climate change. This study aimed to project the potential changes in maternal heat exposure during early pregnancy (3-8 weeks post conception) and the associated burden of congenital heart defects ( CHD s) in the future. Methods and Results This study expanded on a prior nationwide case-control study that evaluated the association between CHD s and maternal heat exposure during early pregnancy in summer and spring. We defined multiple indicators of heat exposure, and applied published odds ratios obtained for the matching season of the baseline (1995-2005) into the projection period (2025-2035) to estimate potential changes in CHD burden throughout the United States. Increases in maternal heat exposure were projected across the United States and to be larger in the summer. The Midwest will potentially have the highest increase in summer maternal exposure to excessively hot days (3.42; 95% CI, 2.99-3.88 per pregnancy), heat event frequency (0.52; 95% CI, 0.44-0.60) and heat event duration (1.73; 95% CI, 1.49-1.97). We also found large increases in specific CHD subtypes during spring, including a 34.0% (95% CI, 4.9%-70.8%) increase in conotruncal CHD in the South and a 38.6% (95% CI , 9.9%-75.1%) increase in atrial septal defect in the Northeast. Conclusions Projected increases in maternal heat exposure could result in an increased CHD burden in certain seasons and regions of the United States.

Using Microsimulation to Estimate the Future Health and Economic Costs of Salmonellosis under Climate Change in Central Queensland, Australia

BACKGROUND

The incidence of salmonellosis, a costly foodborne disease, is rising in Australia. Salmonellosis increases during high temperatures and rainfall, and future incidence is likely to rise under climate change. Allocating funding to preventative strategies would be best informed by accurate estimates of salmonellosis costs under climate change and by knowing which population subgroups will be most affected.

OBJECTIVE

We used microsimulation models to estimate the health and economic costs of salmonellosis in Central Queensland under climate change between 2016 and 2036 to inform preventative strategies.

METHODS

We projected the entire population of Central Queensland to 2036 by simulating births, deaths, and migration, and salmonellosis and two resultant conditions, reactive arthritis and postinfectious irritable bowel syndrome. We estimated salmonellosis risks and costs under baseline conditions and under projected climate conditions for Queensland under the A1FI emissions scenario using composite projections from 6 global climate models (warm with reduced rainfall). We estimated the resulting costs based on direct medical expenditures combined with the value of lost quality-adjusted life years (QALYs) based on willingness-to-pay.

RESULTS

Estimated costs of salmonellosis between 2016 and 2036 increased from 456.0 QALYs (95% CI: 440.3, 473.1) and AUD29,900,000 million (95% CI: AUD28,900,000, AUD31,600,000), assuming no climate change, to 485.9 QALYs (95% CI: 469.6, 503.5) and AUD31,900,000 (95% CI: AUD30,800,000, AUD33,000,000) under the climate change scenario.

CONCLUSION

We applied a microsimulation approach to estimate the costs of salmonellosis and its sequelae in Queensland during 2016-2036 under baseline conditions and according to climate change projections. This novel application of microsimulation models demonstrates the models' potential utility to researchers for examining complex interactions between weather and disease to estimate future costs. https://doi.org/10.1289/EHP1370.

Food-borne disease and climate change in the United Kingdom

This review examined the likely impact of climate change upon food-borne disease in the UK using Campylobacter and Salmonella as example organisms. Campylobacter is an important food-borne disease and an increasing public health threat. There is a reasonable evidence base that the environment and weather play a role in its transmission to humans. However, uncertainty as to the precise mechanisms through which weather affects disease, make it difficult to assess the likely impact of climate change. There are strong positive associations between Salmonella cases and ambient temperature, and a clear understanding of the mechanisms behind this. However, because the incidence of Salmonella disease is declining in the UK, any climate change increases are likely to be small. For both Salmonella and Campylobacter the disease incidence is greatest in older adults and young children. There are many pathways through which climate change may affect food but only a few of these have been rigorously examined. This provides a high degree of uncertainty as to what the impacts of climate change will be. Food is highly controlled at the National and EU level. This provides the UK with resilience to climate change as well as potential to adapt to its consequences but it is unknown whether these are sufficient in the context of a changing climate.

Burden of salmonellosis, campylobacteriosis and listeriosis: a time series analysis, Belgium, 2012 to 2020

Salmonellosis, campylobacteriosis and listeriosis are food-borne diseases. We estimated and forecasted the number of cases of these three diseases in Belgium from 2012 to 2020, and calculated the corresponding number of disability-adjusted life years (DALYs). The salmonellosis time series was fitted with a Bai and Perron two-breakpoint model, while a dynamic linear model was used for campylobacteriosis and a Poisson autoregressive model for listeriosis. The average monthly number of cases of salmonellosis was 264 (standard deviation (SD): 86) in 2012 and predicted to be 212 (SD: 87) in 2020; campylobacteriosis case numbers were 633 (SD: 81) and 1,081 (SD: 311); listeriosis case numbers were 5 (SD: 2) in 2012 and 6 (SD: 3) in 2014. After applying correction factors, the estimated DALYs for salmonellosis were 102 (95% uncertainty interval (UI): 8-376) in 2012 and predicted to be 82 (95% UI: 6-310) in 2020; campylobacteriosis DALYs were 1,019 (95% UI: 137-3,181) and 1,736 (95% UI: 178-5,874); listeriosis DALYs were 208 (95% UI: 192-226) in 2012 and 252 (95% UI: 200-307) in 2014. New actions are needed to reduce the risk of food-borne infection with Campylobacter spp. because campylobacteriosis incidence may almost double through 2020.

Developing Health-Related Indicators of Climate Change: Australian Stakeholder Perspectives

Climate-related health indicators are potentially useful for tracking and predicting the adverse public health effects of climate change, identifying vulnerable populations, and monitoring interventions. However, there is a need to understand stakeholders’ perspectives on the identification, development, and utility of such indicators. A qualitative approach was used, comprising semi-structured interviews with key informants and service providers from government and non-government stakeholder organizations in South Australia. Stakeholders saw a need for indicators that could enable the monitoring of health impacts and time trends, vulnerability to climate change, and those which could also be used as communication tools. Four key criteria for utility were identified, namely robust and credible indicators, specificity, data availability, and being able to be spatially represented. The variability of risk factors in different regions, lack of resources, and data and methodological issues were identified as the main barriers to indicator development. This study demonstrates a high level of stakeholder awareness of the health impacts of climate change, and the need for indicators that can inform policy makers regarding interventions.

Impacts of ambient temperature on the burden of bacillary dysentery in urban and rural Hefei, China

Bacillary dysentery continues to be a major health issue in developing countries and ambient temperature is a possible environmental determinant. However, evidence about the risk of bacillary dysentery attributable to ambient temperature under climate change scenarios is scarce. We examined the attributable fraction (AF) of temperature-related bacillary dysentery in urban and rural Hefei, China during 2006-2012 and projected its shifting pattern under climate change scenarios using a distributed lag non-linear model. The risk of bacillary dysentery increased with the temperature rise above a threshold (18·4 °C), and the temperature effects appeared to be acute. The proportion of bacillary dysentery attributable to hot temperatures was 18·74% (95 empirical confidence interval (eCI): 8·36-27·44%). Apparent difference of AF was observed between urban and rural areas, with AF varying from 26·87% (95% eCI 16·21-36·68%) in urban area to -1·90% (95 eCI -25·03 to 16·05%) in rural area. Under the climate change scenarios alone (1-4 °C rise), the AF from extreme hot temperatures (>31·2 °C) would rise greatly accompanied by the relatively stable AF from moderate hot temperatures (18·4-31·2 °C). If climate change proceeds, urban area may be more likely to suffer from rapidly increasing burden of disease from extreme hot temperatures in the absence of effective mitigation and adaptation strategies.

Projections of hepatitis A virus infection associated with flood events by 2020 and 2030 in Anhui Province, China

Assessing and responding to health risk of climate change is important because of its impact on the natural and societal ecosystems. More frequent and severe flood events will occur in China due to climate change. Given that population is projected to increase, more people will be vulnerable to flood events, which may lead to an increased incidence of HAV infection in the future. This population-based study is going to project the future health burden of HAV infection associated with flood events in Huai River Basin of China. The study area covered four cities of Anhui province in China, where flood events were frequent. Time-series adjusted Poisson regression model was developed to quantify the risks of flood events on HAV infection based on the number of daily cases during summer seasons from 2005 to 2010, controlling for other meteorological variables. Projections of HAV infection in 2020 and 2030 were estimated based on the scenarios of flood events and demographic data. Poisson regression model suggested that compared with the periods without flood events, the risks of severe flood events for HAV infection were significant (OR = 1.28, 95 % CI 1.05-1.55), while risks were not significant from moderate flood events (OR = 1.16, 95 % CI 0.72-1.87) and mild flood events (OR = 1.14, 95 % CI 0.87-1.48). Using the 2010 baseline data and the flood event scenarios (one severe flood event), increased incidence of HAV infection were estimated to be between 0.126/10⁵ and 0.127/10⁵ for 2020. Similarly, the increased HAV infection incidence for 2030 was projected to be between 0.382/10⁵ and 0.399/10⁵. Our study has, for the first time, quantified the increased incidence of HAV infection that will result from flood events in Anhui, China, in 2020 and 2030. The results have implications for public health preparation for developing public health responses to reduce HAV infection during future flood events.

Forecasted Impact of Climate Change on Infectious Disease and Health Security in Hawaii by 2050

OBJECTIVE

Climate change is expected to cause extensive shifts in the epidemiology of infectious and vector-borne diseases. Scenarios on the effects of climate change typically attribute altered distribution of communicable diseases to a rise in average temperature and altered incidence of infectious diseases to weather extremes.

METHODS

Recent evaluations of the effects of climate change on Hawaii have not explored this link. It may be expected that Hawaii's natural geography and robust water, sanitation, and health care infrastructure renders residents less vulnerable to many threats that are the focus on smaller, lesser developed, and more vulnerable Pacific islands. In addition, Hawaii's communicable disease surveillance and response system can act rapidly to counter increases in any disease above baseline and to redirect resources to deal with changes, particularly outbreaks due to exotic pathogens.

RESULTS

The evidence base examined in this article consistently revealed very low climate sensitivity with respect to infectious and mosquito-borne diseases.

CONCLUSIONS

A community resilience model is recommended to increase adaptive capacity for all possible climate change impacts rather an approach that focuses specifically on communicable diseases. (Disaster Med Public Health Preparedness. 2016;10:797-804).

Quantitative analysis of burden of bacillary dysentery associated with floods in Hunan, China

BACKGROUND

Jishou and Huaihua, two cities in the west of Hunan Province, had suffered from severe floods because of long-lasting and heavy rainfall during the end of June and July 2012. However, the Disability Adjusted of Life Years (DALYs) of bacillary dysentery caused by the floods have not been examined before. The study aimed to quantify the impact of the floods on the burden of bacillary dysentery in Hunan, China.

METHODS

A unidirectional case-crossover study was firstly conducted to determine the relationship between daily cases of bacillary dysentery and the floods in Jishou and Huaihua of Hunan Province in 2012. Odds ratios (ORs) estimated by conditional logistic regression were used to quantify the risk of the floods on the disease. The years lived with disability (YLDs) of bacillary dysentery attributable to floods were then estimated based on the WHO framework to calculate potential impact fraction in the Burden of Disease study.

RESULTS

Multivariable analysis showed that floods were significantly associated with an increased risk of the number of cases of bacillary dysentery (OR=3.270, 95% CI: 1.299-8.228 in Jishou; OR=2.212, 95% CI: 1.052-4.650 in Huaihua). The strongest effect was shown with a 1-day lag in Jishou and a 4-day lag in Huaihua. Attributable YLD per 1000 of bacillary dysentery due to the floods was 0.0296 in Jishou and 0.0157 in Huaihua.

CONCLUSIONS

Our study confirms that floods have significantly increased the risks of bacillary dysentery in the study areas. In addition, a sudden and severe flooding with a shorter duration may cause more burdens of bacillary dysentery than a persistent and moderate flooding. Public health preparation and intervention programs should be taken to reduce and prevent a potential risk of bacillary dysentery epidemics after floods.

Identifying Flood-Related Infectious Diseases in Anhui Province, China: A Spatial and Temporal Analysis

The aim of this study was to explore infectious diseases related to the 2007 Huai River flood in Anhui Province, China. The study was based on the notified incidences of infectious diseases between June 29 and July 25 from 2004 to 2011. Daily incidences of notified diseases in 2007 were compared with the corresponding daily incidences during the same period in the other years (from 2004 to 2011, except 2007) by Poisson regression analysis. Spatial autocorrelation analysis was used to test the distribution pattern of the diseases. Spatial regression models were then performed to examine the association between the incidence of each disease and flood, considering lag effects and other confounders. After controlling the other meteorological and socioeconomic factors, malaria (odds ratio [OR] = 3.67, 95% confidence interval [CI] = 1.77-7.61), diarrhea (OR = 2.16, 95% CI = 1.24-3.78), and hepatitis A virus (HAV) infection (OR = 6.11, 95% CI = 1.04-35.84) were significantly related to the 2007 Huai River flood both from the spatial and temporal analyses. Special attention should be given to develop public health preparation and interventions with a focus on malaria, diarrhea, and HAV infection, in the study region.

Seasonal variation of bacterial communities in shellfish harvesting waters: preliminary study before applying phage therapy

The recurrent emergence of infections outbreaks associated with shellfish consumption is an important health problem, which results in substantial economic losses to the seafood industry. Even after depuration, shellfish is still involved in outbreaks caused by pathogenic bacteria, which increases the demand for new efficient strategies to control the shellfish infection transmission. Phage therapy during the shellfish depuration is a promising approach, but its success depends on a detailed understanding of the dynamics of bacterial communities in the harvesting waters. This study intends to evaluate the seasonal dynamics of the overall bacterial communities, disease-causing bacterial populations and bacterial sanitary quality indicators in two authorized harvesting-zones at Ria de Aveiro. During the hot season, the total bacterial community presented high complexity and new prevalent populations of the main shellfish pathogenic bacteria emerged. These results indicate that the spring/summer season is a critical period during which phage therapy should be applied.

Salmonella vaccines: lessons from the mouse model or bad teaching?

Salmonella enterica subsp. enterica includes several very important human serovars including Typhi, Paratyphi, Typhimurium and Enteritidis. These bacteria cause a significant global burden of disease, typically classified into enteric fever, gastroenteritis and, more recently, invasive non-typhoidal salmonellosis (iNTS). Vaccines have been developed for one of these serovars, S. Typhi and the recent increase in iNTS cases has resulted in a push to develop new vaccines that will inhibit disease by S. Typhimurium and S. Enteritidis, the most common iNTS S. enterica serovars. The development of new human vaccines has been informed by studies in the murine model of typhoid fever based on S. Typhimurium infections of very 'sensitive' (Nramp-1(S)) mice, which has some obvious deficiencies, not the least that antibodies protect humans against S. Typhi infection but are only weakly protective in 'sensitive' mice infected with S. Typhimurium. S. Typhimurium also lacks Vi, the target of protective antibodies in typhoid fever. Notwithstanding these deficiencies, the murine model has identified a very complex series of innate and adaptive immune responses to infection that might be exploited to develop new vaccines. Equally, advances in understanding the pathogenesis of infection, through pathogenomics and more sophisticated animal models will likely contribute to the development of novel immunogens.

Climate variability, weather and enteric disease incidence in New Zealand: time series analysis

BACKGROUND

Evaluating the influence of climate variability on enteric disease incidence may improve our ability to predict how climate change may affect these diseases.

OBJECTIVES

To examine the associations between regional climate variability and enteric disease incidence in New Zealand.

METHODS

Associations between monthly climate and enteric diseases (campylobacteriosis, salmonellosis, cryptosporidiosis, giardiasis) were investigated using Seasonal Auto Regressive Integrated Moving Average (SARIMA) models.

RESULTS

No climatic factors were significantly associated with campylobacteriosis and giardiasis, with similar predictive power for univariate and multivariate models. Cryptosporidiosis was positively associated with average temperature of the previous month (β =  0.130, SE =  0.060, p <0.01) and inversely related to the Southern Oscillation Index (SOI) two months previously (β =  -0.008, SE =  0.004, p <0.05). By contrast, salmonellosis was positively associated with temperature (β  = 0.110, SE = 0.020, p<0.001) of the current month and SOI of the current (β  = 0.005, SE = 0.002, p<0.050) and previous month (β  = 0.005, SE = 0.002, p<0.05). Forecasting accuracy of the multivariate models for cryptosporidiosis and salmonellosis were significantly higher.

CONCLUSIONS

Although spatial heterogeneity in the observed patterns could not be assessed, these results suggest that temporally lagged relationships between climate variables and national communicable disease incidence data can contribute to disease prediction models and early warning systems.