Three Major Types Of Infectious Diseases And Their Associations With Meteorological Factors

BackgroundMeteorological factors have considerable effects on human health, industrial production and the social development. Previous literature showed the significant effects of meteorological factors on infectious diseases. China has established the surveillance system of infectious diseases to check and control the morbidity and mortality of diseases, but some provinces keep suffering from the potential threat. For example, China is one of the first three countries with most tuberculosis (TB) cases. Besides, the large population, unbalanced economic development and the large area with various climates from temperate to tropical climate contribute to the potential outbreak of these diseases in China. Additionally, Guangdong as the largest province in southern China has subtropical and tropical climate with high ambient temperature, relative humidity, which indeed provide a comfortable environment for the development and transmission of infectious diseases. Therefore, it is meaningful to make a further analysis of meteorological effects on infectious diseases in Guangdong, and in China.This study focused on malaria, hand, food, and mouth disease (HFMD) and TB, chosen by the prevalence, importance, and representativeness of infectious diseases. Malaria and tuberculosis, following Human Immunodeficiency Virus (HIV) are the first three infectious diseases in the world. Malaria represents the typical kind of vector-borne diseases, which contributes a lot to the study of meteorological effects on diseases occurrence by working on mosquitoes’activities and behaviors. TB, as a kind of chronic air-borne diseases, has been one of the biggest problems in the field of medical science for centuries. Additionally, HFMD has the highest incidence among class C infectious diseases in Guangdong province, and can outbreak easily, which make it become one of the most important diseases. Therefore, this study chooses malaria, HFMD, and TB as three major infectious diseases to analyze the meteorological effects.Infectious diseases have obvious seasonality, which is caused mainly by the meteorological factors. Previous studies focused on the temporal analysis using ARIMA and its derived models as well as linear regression models, but these methods restricted the number of lags and the linear hypothesis may be inappropriate. Also, because of lack of enough data, some subgroup analyses cannot be conducted to detect the different sensitivity of subpopulation to meteorological effects. Furthermore, there is geographical heterogeneity in such effects, which is closely associated with the spatial patterns of infectious diseases.This study intends to analyze the meteorological effects on three major types of infectious diseases, including malaria, HFMD and TB. Firstly, this study wants to analyze the associations between meteorological factors and malaria, and conduct the subgroup analyses among different populations. Besides, this study will conduct the multicenter research to show the meteorological effects on HFMD, and explore the heterogeneity of these effects. Thirdly, this study wants to analyze the spatiotemporal distribution of TB and detect the associated factors at the demographic, socio-economic and health care level to provide rational and scientific evidence for authorities to make strategies.Method2.1 The Study of meteorological effects on malaria.Guangdong province is situated at the southernmost tip of mainland China. Guangdong has a population of 106 million residing in a land area of 179,612 sq km and a sub-tropical, marine, monsoon climate with an annual average temperature of 22℃ and annual average rainfall of 1,500 mm. The China Meteorological Data Sharing Service System provided the daily meteorological measures, including average/minimum/maximum temperature (℃), cumulative duration of sunshine (hours/week), cumulative precipitation (mm/week), average/maximum/extreme wind speed (m/s), average/minimum/maximum atmospheric pressure (hPa), and average relative humidity (%).In mainland China, each individual case of notable disease including malaria must be reported to the Chinese Centre for Disease Control and Prevention (CCDC) through the online Infection Diseases Monitor Information System. The data of all reported malaria cases in Guangdong during the period from 1 January,2005 to 31 December,2013 was obtained.The Granger causality Wald test and Spearman correlation analysis were employed to select climatic variables influencing malaria. The distributed lag non-linear model (DLNM) was used to estimate the non-linear and delayed effects of weekly temperature, duration of sunshine, and precipitation on the weekly number of malaria cases after controlling for other confounders. Stratified analyses were conducted to identify the sub-population’s susceptibility to meteorological effects by malaria type, gender, and age group.2.2 The study of meteorological effects on HFMD.The study site is eight cities in Guangdong, including Guangzhou, Shaoguan, Shantou, Heyuan, Yangjiang, Guangning, Luoding, and Xuwen. The daily meteorological factors in each cities were obtained from China Meteorological Data Sharing Service System. The daily HFMD cases during 1 January,2009 to 31 December,2013 were obtained from CCDC. Demographic data, including population density (persons per square km), the ratio of male to female population, the ratio of children under five years old (%), Gross Domestic Product (GDP) per capita (RMB), living space per capita (square meter), and the ratio of population flow (%) were collected from the Sixth National Population Census of China in 2010.Based on daily time-series data in eight major cities in Guangdong, China during 2009-2013, mixed generalized additive models were employed to estimate city-specific meteorological effects on pediatric HFMD. Then, a random-effect multivariate meta-analysis was conducted to obtain the pooled risks and to explore heterogeneity explained by city-level factors.2.3 Spatiotemporal distribution of TB and its associated factorsThe study site is 31 cities of mainland China, excluding Taiwan, Hong Kong and Macao. The monthly meteorological factors were collected from China Meteorological Data Sharing Service System. CCDC also provided the monthly TB cases during the period of January,2005 to December,2012. National Bureau of statistics of China provided the yearly demographic data in 2005-2012, which includes Gross Domestic Product (GDP) per capita (100000 RMB), number of elderly (per 1000), number of doctors (per 1000), number of hospitals, number of beds in health care institutions (per 1000) and the number of persons with high education (per 1000).Global Moran’s I index and Getis-Ord General G were used to investigate the global spatial autocorrelation of TB incidence. Both the local Moran’s I index and Getis-Ord Gi were employed to detect the local clustering provinces with high prevalence. The spatiotemporal scan test can investigate the spatiotemporal clustering during the study period. In the end, this study made a further analysis of the influencing factors of TB based on the Poisson mixed model.The descriptive analysis and modelling process were based on R 3.2.4, the spatial analysis and visual map were made through ArcGIS 10.1,and the spatiotemporal analysis was conducted using SaTScan 9.4.2 software.Results3.1 The study of meteorological effects on malaria.An incidence rate of 1.1 cases per 1000000 people was detected in Guangdong from 2005-2013. High temperature was associated with an observed immediate increase in malaria incidence, with the effect lasting for four weeks and a maximum relative risk (RR) of 1.57 (95% confidence interval (CI):1.06-2.33) by comparing 30℃ to the median temperature. The effect of sunshine duration peaked at lag five and the maximum RR was 1.36 (95% CI:1.08-1.72) by comparing 24 hours/week to 0 hours/week. A J-shaped relationship was found between malaria incidence and precipitation with a threshold of 150 mm/week. Over the threshold, precipitation after four weeks increased malaria incidence with the effect lasting for 15 weeks, and the maximum RR of 1.55 (95% CI:1.18-2.03) occurring at lag eight by comparing 225 mm/week to 0 mm/week. Plasmodium falciparum was more sensitive to temperature and precipitation than Plasmodium vivax. Females had a higher susceptibility to the effects of sunshine and precipitation, and children and the elderly were more sensitive to the change of temperature, sunshine duration, and precipitation.3.2 The study of meteorological effects on HFMD.An total of 400408 pediatric HFMD cases were found and the annual incidence rate is 17 cases per 1000 children. Spearman rank correlation showed that there were significant and negative associations between atmospheric pressure and average temperature and the precipitation was also significantly associated with relative humidity. Average temperature was positively associated with pediatric HFMD cases with the highest pooled RR of 1.52 (95% CI:1.30-1.77) at 30.5℃ as compared to the median temperature (23.5℃). Significant positive non-linear effects of high relative humidity were also observed with a 13% increase (RR=1.13,95% CI:1.00-1.28) in the risk of HFMD at a relative humidity of 86.9% as compared to the median value (78%). The effect estimates showed geographic variations among the cities which was significantly associated with city’s latitude and longitude with an explained heterogeneity of 32%.3.3 Spatiotemporal distribution of TB and its associated factorsAn total of 8693450 TB cases of mainland China in January,2005-December, 2012 were collected. There were significant global spatial autocorrelations in each year during the study period and the local spatial autocorrelation analysis showed that cites with high TB incidence clustered in Northwest districts (mainly including Xinjiang, Tibet and Qinghai) and South districts (mainly including Guizhou, Hunan and Chongqing). While the low incidence area clustered around Ynagtze River delta, including Beijing, Heibei, Jiangsu, Shanghai and Zhejiang. Spatiotemporal scan test indicated that the Xinjiang, Ningxia, Qinghai, Gansu, Shaanxi, Sichuan, Hubei, Chongqing, Tibet, Hunan, Guizhou, Yunnan, Guangxi, Hainan, Mongolia, Shanxi and Henan had the highest possibility of clustering during January,2005 to October 2008. Heilongjiang was second clustering province during January,2005-July,2008. Multiple Poisson mixed model demonstrated that GDP per capita (RR=0.876,95CI: 0.855-0.897), number of doctors (RR=0.987,95CI:0.987-0.987), and monthly average temperature (RR=0.973,95CI:0.972-0.974) were negatively associated with TB morbidity. The TB incidence increased 81.8% when the number of elderly increased 1 per 1000 persons (RR=1.818,95CI:1.576-2.097); TB incidence increased 3.2% as the monthly average wind speed increased 0.1 m/s (RR=1.032, 95CI:1.013-1.051); and TB incidence increased 1.3% if the relative humidity increased 0.1%(RR=1.013,95CI:1.012-1.014).Conclusions(1) Malaria, HFMD and TB are the public health threats worldwide.(2) Malaria clustered in male adults and HFMD clustered in male and children under three years old.(3) Temperature, duration of sunshine and precipitation played important roles in malaria incidence with effects delayed and varied across lags. Climatic effects were also distinct among subgroups.(4) Temperature and relative humidity had an delayed and nonlinear effects on HFMD and temperature, relative humidity and wind speed were associated with TB.(5) The heterogeneity of meteorological effects on HFMD was related to the latitude and longitude.(6) TB incidence clustered in Northwest and south districts of mainland China.(7) This study provided helpful and scientific evidence for predicting and controlling malaria, HFMD and TB, as well as developing the future warning system.