Effect of Non-Stationary Climate on Infectious Gastroenteritis Transmission in Japan

by Allison Hu

Infectious gastroenteritis, otherwise known as the stomach flu, is a medical condition from inflammation of the gastrointestinal tract that involves both the stomach and the small intestine, causing a combination of diarrhea, vomiting, and abdominal pain and cramping. This common disease contributes significantly to the 1 billion episodes of diarrhea and 3 million deaths in children under 5 years of age per year, and is the fifth-leading cause of death worldwide (Onozuka et al. 2014). The transmission of infectious gastroenteritis is rather complex, involving both host and environmental factors.

Environmental factors such as temperature, humidity, and rainfall are widely considered as important factors in the spread and seasonality of infectious gastroenteritis (Konno et al. 1983). Additionally, several studies reported that the El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) play important roles in the transmission of infectious diseases – including dengue (Thai et al. 2010), malaria (Hashizume et al. 2012) and cholera (Hashizume et al. 2013).

The ENSO is a naturally occurring phenomenon that involves fluctuating ocean temperatures in the equatorial Pacific. This phenomenon is the most dominant force causing variations in regional climate patterns, which affects weather conditions such as temperature, rainfall, wind speed and direction, and storm tracking throughout the world. The pattern generally varies from region to region and fluctuates between two states: warmer than normal central and eastern equatorial Pacific SSTs (El Niño) and cooler than normal central and eastern equatorial Pacific SSTs (La Niña) (Shaman et al. 2013).

The IOD is a coupled ocean and atmosphere phenomenon in the equatorial Indian Ocean that affects the climate of Australia and other countries that surround the Indian Ocean basin (Saji et al. 1999). A positive IOD period is characterized by cooler than normal water in the tropical eastern Indian Ocean and warmer than normal water in the tropical western Indian Ocean. A positive IOD SST pattern has been shown to be associated with a decrease in rainfall over parts of central and southern Australia. Conversely, a negative IOD period is characterized by warmer than normal water in the tropical eastern Indian Ocean and cooler than normal water in the tropical western Indian Ocean. A negative IOD SST pattern has been shown to be associated with an increase in rainfall over parts of southern Australia. Moreover, the World Health Organization (WHO) quantified the impact of global warming on diarrhea, and reported that warming by 1oC was associated with a 5% increase in diarrhea (Hashizume et al. 2012). Although regional differences and contrasting effects of temperature on different kinds of diarrhea are evident, few studies have examined the non-stationary relationships between global climatic variability and infectious gastroenteritis.

Onozuka therefore explored the time-varying relationship between climate variation and monthly incidence of infectious gastroenteritis between 2000 and 2012 in Fukuoka, Japan using cross-wavelet coherency analysis to assess the pattern of associations between indices for the Indian Ocean Dipole (IOD) and the El Nino Southern Oscillation (ENSO). Wavelet analysis is useful in the investigation of non-stationary associations using time series data as it can measure associations between two time-series at any frequency band and time-window period (Torrance et al. 1998). This analysis has been used to determine whether the presence of a particular periodic cycle at a given time in disease incidence corresponds to the presence of the same periodical cycle at the same time in an exposure covariate. Wavelet analyses have also previously been used to analyze the transmission of infectious diseases (Cazelles et al. 2005). Therefore, a better understanding of the sensitivity of these analyses to climate variability can potentially contribute to developing a reliable climate-based prediction system for gastroenteritis epidemics. Onozuka was able to report the first ever quantification of the time-varying impact of climatic factors on the number of infectious gastroenteritis cases using cross-wavelet analysis.

Analysis demonstrated that infectious gastroenteritis cases were non-stationary and significantly associated with the IOD and ENSO for a period of approximately one to two years (Onozuka et al. 2014). Results therefore not only demonstrated the positive correlation between climate change and the spread of infectious gastroenteritis but also the importance of global climate factors such as IOD and ENSO on the transmission of infectious gastroenteritis. Lastly, Onozuka found that the incidence of infectious gastroenteritis is strongly associated with local weather factors such as temperature, relative humidity, and rainfall, with coherent cycles throughout the year. Furthermore, relative humidity and rainfall also affect water and sanitation infrastructure and the number of pathogens, and might impact the replication rate of certain bacterial and viral pathogens that contribute to the “host factor” of the disease.

Results of this study have practical implications for public health officials. Elucidation of the relationship between climate variability and infectious gastroenteritis transmission is important for disease control and prevention. These findings may be beneficial in helping public health officials predict epidemics and prepare for the effects of climatic change on infectious gastroenteritis through the implementation of preventative public health measures. Early warning systems for epidemics of infectious gastroenteritis should consider non-stationary, and possibly non-linear patterns of association between climatic factors and infectious gastroenteritis cases.

Onozuka, D., 2014. Effect of non-stationary climate on infectious gastroenteritis transmission in Japan. Scientific reports, 4.

Konno, T., Suzuki, H., Katsushima, N., Imai, A., Tazawa, F., Kutsuzawa, T., … & Ishida, N., 1983. Influence of temperature and relative humidity on human rotavirus infection in Japan. Journal of Infectious Diseases 147, 125-128.

Thai, K. T., Cazelles, B., Van Nguyen, N., Vo, L. T., Boni, M. F., Farrar, J., … & de Vries, P. J., 2010. Dengue dynamics in Binh Thuan province, southern Vietnam: periodicity, synchronicity and climate variability. PLoS Neglected Tropical Diseases 4, 747.

Hashizume, M., Chaves, L. F., & Minakawa, N., 2012. Indian Ocean Dipole drives malaria resurgence in East African highlands. Scientific Reports 2. 

Hashizume, M., Chaves, L. F., Faruque, A. S. G., Yunus, M., Streatfield, K., & Moji, K., 2013. A differential effect of Indian ocean dipole and El Niño on cholera dynamics in Bangladesh. PloS one 8, 60001.

Shaman, J., & Lipsitch, M., 2013. The El Niño–Southern Oscillation (ENSO)–pandemic Influenza connection: Coincident or causal?. Proceedings of the National Academy of Sciences 110, 3689-3691.

Saji, N. H., Goswami, B. N., Vinayachandran, P. N., & Yamagata, T., 1999. A dipole mode in the tropical Indian Ocean. Nature 401, 360-363.

Torrence, C., & Compo, G. P., 1998. A practical guide to wavelet analysis. Bulletin of the American Meteorological Society 79, 61-78.

Cazelles, B., Chavez, M., McMichael, A. J., & Hales, S., 2005. Nonstationary influence of El Nino on the synchronous dengue epidemics in Thailand. PLoS Medicine 2, 106.

http://www.nature.com/srep/2014/140603/srep05157/full/srep05157.html?WT.ec_id=SREP-20140610

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