Spatial and temporal variation in the association between temperature and salmonellosis in NZ

Climate Change and Cascading Risks from Infectious Disease

Climate change is adversely affecting the burden of infectious disease throughout the world, which is a health security threat. Climate-sensitive infectious disease includes vector-borne diseases such as malaria, whose transmission potential is expected to increase because of enhanced climatic suitability for the mosquito vector in Asia, sub-Saharan Africa, and South America. Climatic suitability for the mosquitoes that can carry dengue, Zika, and chikungunya is also likely to increase, facilitating further increases in the geographic range and longer transmission seasons, and raising concern for expansion of these diseases into temperate zones, particularly under higher greenhouse gas emission scenarios. Early spring temperatures in 2018 seem to have contributed to the early onset and extensive West Nile virus outbreak in Europe, a pathogen expected to expand further beyond its current distribution, due to a warming climate. As for tick-borne diseases, climate change is projected to continue to contribute to the spread of Lyme disease and tick-borne encephalitis, particularly in North America and Europe. Schistosomiasis is a water-borne disease and public health concern in Africa, Latin America, the Middle East, and Southeast Asia; climate change is anticipated to change its distribution, with both expansions and contractions expected. Other water-borne diseases that cause diarrheal diseases have declined significantly over the last decades owing to socioeconomic development and public health measures but changes in climate can reverse some of these positive developments. Weather and climate events, population movement, land use changes, urbanization, global trade, and other drivers can catalyze a succession of secondary events that can lead to a range of health impacts, including infectious disease outbreaks. These cascading risk pathways of causally connected events can result in large-scale outbreaks and affect society at large. We review climatic and other cascading drivers of infectious disease with projections under different climate change scenarios. Supplementary file1 (MP4 328467 KB).

Effect of Temperature and Rainfall on Sporadic Salmonellosis Notifications in Melbourne, Australia 2000-2019: A Time-Series Analysis

Weather can impact infectious disease transmission, particularly for heat-sensitive pathogens, such as Salmonella. We conducted an ecological time-series analysis to estimate short-term associations between nonoutbreak-related notifications of Salmonella and weather conditions-temperature and rainfall-in Melbourne, Australia from 2000 to 2019. Distributed lag nonlinear models were created to analyze weather-salmonellosis associations and potential lag times on a weekly time scale, controlling for seasonality and long-term trends. Warmer temperatures were associated with increased risk of notification. Effects were temporally lagged, with the highest associations observed for warm temperatures 2-6 (greatest at 4) weeks before notification. The overall estimated relative risk of salmonellosis increased twofold at 33°C compared to the average weekly temperature (20.35°C) for the 8-week period preceding the disease notification. For Salmonella Typhimurium alone, this occurred at temperatures over 32°C. There were no statistically significant associations with rainfall and notification rates in any of the analyses performed. This study demonstrates the short-term influences of warm temperatures on Salmonella infections in Melbourne over a 20-year period. Salmonelloses are already the second most notified gastrointestinal diseases in Victoria, and these findings suggest that notifications may increase with increasing temperatures. This evidence contributes to previous findings that indicate concerns for public health with continued warm weather.

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.

Climate change and infectious diseases in Australia's Torres Strait Islands

OBJECTIVE

This research seeks to identify climate-sensitive infectious diseases of concern with a present and future likelihood of increased occurrence in the geographically vulnerable Torres Strait Islands, Australia. The objective is to contribute evidence to the need for adequate climate change responses.

METHODS

Case data of infectious diseases with proven, potential and speculative climate sensitivity were compiled.

RESULTS

Five climate-sensitive diseases in the Torres Strait and Cape York region were identified as of concern: tuberculosis, dengue, Ross River virus, melioidosis and nontuberculous mycobacterial infection. The region constitutes 0.52% of Queensland's population but has a disproportionately high proportion of the state's cases: 20.4% of melioidosis, 2.4% of tuberculosis and 2.1% of dengue.

CONCLUSIONS

The Indigenous Torres Strait Islander peoples intend to remain living on their traditional country long-term, yet climate change brings risks of both direct and indirect human health impacts. Implications for public health: Climate-sensitive infections pose a disproportionate burden and ongoing risk to Torres Strait Islander peoples. Addressing the causes of climate change is the responsibility of various agencies in parallel with direct action to minimise or prevent infections. All efforts should privilege Torres Strait Islander peoples' voices to self-determine response actions.

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.

Waterborne Diseases Arising From Climate Change

As a result of increased frequency and intensity of heat waves, increased floods and droughts, change in climate will affect biological, physical, and chemical components of water through different paths thus enhancing the risk of waterborne diseases. Identifying the role of weather in waterborne infection is a priority public health research issue as climate change is predicted to increase the frequency of extreme precipitation and temperature events. This chapter provides evidence that precipitation and temperature can affect directly or indirectly water quality and consequently affect the health human. This chapter also highlights the complex relationship between precipitation or temperature and transmission of waterborne disease such as diarrheal disease, gastroenteritis, cryptosporidiosis, giardiasis, and cholera.

Climate variability and salmonellosis in Singapore - A time series analysis

Climate change is expected to bring about global warming and an increase in the frequency of extreme weather events. This may consequently influence the transmission of food-borne diseases. The short term associations between climatic conditions and Salmonella infections are well documented in temperate climates but not in the tropics. We conducted an ecological time series analysis to estimate the short term associations between non-outbreak, non-travel associated reports of Salmonella infections and observed climatic conditions from 2005 to 2015 for Singapore. We used a negative binomial time series regression model to analyse the associations on a weekly scale, controlling for season, long term trend, delayed weather effects, autocorrelation and the period where Salmonella was made legally notifiable. There were a total of 11,324 Salmonella infections reported during our study period. A 1 °C increase in mean ambient air temperature was associated with a 4.3% increase (Incidence Rate Ratio [IRR]: 1.043, 95% confidence interval [CI] = 1.003, 1.084) in reported Salmonella infections in the same week and a 6.3% increase (IRR: 1.063, 95% CI = 1.022, 1.105) three weeks later. A 1% increase in the mean relative humidity was associated with a 1.3% decrease (IRR: 0.987, 95% CI = 0.981, 0.994) in cases six weeks later, while a 10 mm increase in weekly cumulative rainfall was associated with a 0.8% increase (IRR: 1.008, 95% CI = 1.002, 1.015) in cases 2 weeks later but a 0.9% decrease (IRR: 0.991, 95% CI = 0.984, 0.998) in cases 5 weeks later. No thresholds for these weather effects were detected. This study confirms the short-term influence of climatic conditions on Salmonella infections in Singapore and the potential impact of climate change on Salmonellosis in the tropics.

Spatial variation of heat-related morbidity: A hierarchical Bayesian analysis in multiple districts of the Mekong Delta Region

This study examined spatial variability of heat-related morbidity in multiple districts of the Mekong Delta Region (MDR), Vietnam. It was conducted in 132 district/cities of the MDR. We used a series of hierarchical Bayesian models to examine the region-wide and district-specific association between temperatures and hospitalizations during the period of 2010-2013. The potential effects of seasonality, long-term trends, day of the week and holidays were controlled in the models. We also examined influences of socio-demographic factors on the temperature-hospitalization relationship. The results indicate that an increase of 5 °C in average temperature was associated with a 6.1% increase (95%CI: 5.9, 6.2) in region-wide hospital admissions. However, the district-level risks ranged from a 55.2% decrease {95%CI: (-54), (-56)} to a 24.4% increase (24.3-24.6) in admissions per 5 °C increase in average temperature. This reflects the heterogeneous magnitudes of temperature-hospitalization risk across districts. The results also indicate that temperature-hospitalization risk increased by 1.3% (95%CI: 1.2-1.4), for each increase of 1000 persons/km² in population density, 2.1% (95%CI: 2.04-2.11) for each 1% increase in percent of females, and 2.7% (95%CI: 2.6-2.8) for each 1% increase in percent of pre-school students. In contrast, the temperature-related hospitalization risk decreased up to 6.8% {(95%CI: (-6.6)-(-6.9)} for each 1% increase in rural population. Public health intervention measures for both short-term and long-term effects of heat-related health risk should be developed with consideration of the use of city/district scale for the factors rather than the province scale. The province scale of factors does not accurately represent the variability of health risk due to exposure to high temperatures.

Heatwave and risk of hospitalization: A multi-province study in Vietnam

The effects of heatwaves on morbidity in developing and tropical countries have not been well explored. The purpose of this study was to examine the relationship between heatwaves and hospitalization and the potential influence of socio-economic factors on this relationship in Vietnam. Generalized Linear Models (GLM) with Poisson family and Distributed Lag Models (DLM) were applied to evaluate the effect of heatwaves for each province (province-level effect). A random-effects meta-analysis was applied to calculate the pooled estimates (country-level effects) for 'all causes', infectious, cardiovascular, and respiratory admissions queried by lag days, regions, sex, and ages. We used random-effects meta-regression to explore the potential influence of socio-economic factors on the relationship between heatwaves and hospitalization. The size of province-level effects varied across provinces. The pooled estimates show that heatwaves were significantly associated with a 2.5% (95%CI: 0.8-4.3) and 3.8% (95%CI, 1.5-6.2) increase in all causes and infectious admissions at lag 0. Cardiovascular and respiratory admissions (0.8%, 95%CI: -1.6-3.3; 2.2%, 95%CI: -0.7-5.2) were not significantly increased after a heatwave event. The risk of hospitalization due to heatwaves was higher in the North than in the South for all causes (5.4%, 95%CI: -0.1-11.5 versus 1.3%, 95%CI: 0.1-2.6), infectious (11.2%, 95%CI: 3.1-19.9 versus 3.2%, 95%CI: 0.7-5.7), cardiovascular (7.5%, 95%CI: 1.1-14.4 versus -1.2%, 95%CI: -2.6-2.3), and respiratory diseases (2.7%, 95%CI: -5.4-11.5 versus 2.1%, 95%CI: -0.8-1.2). A non-significant influence of socio-economic factors on the relationship between heatwave and hospitalization was observed. This study provides important evidence and suggests implications for the projected impacts of climate change related extreme weather. Climate change adaptation programs of the health sector should be developed to protect residents from the effects of extreme weather events such as heatwaves in Vietnam.