| BackgroundThe present climate and environment change have increased, which was caused by human activities. With the increasing of global climate anomaly, climate change is the biggest global health threat of the 21st century. The summit focused on climate change on Asian Pacific Economic Cooperation and the G20 in 2014. The politicians reached a consensus that the human survival and development has been effected by global climate change deeply, therefore it becomes a major challenge for all countries in the world. One feature of climate change is that the frequency and intensity of extreme weather events will change. Due to climate change, an increase of various natural disasters in frequency and intensity was observed in the 20th century, and rainstorm floods are recognized as the most frequent and devastating type of natural disasters in the world. On average, floods accounted for 40-50% of the disasters in the world. Flooding is a geological disaster resulting from the overflowing of a river or the temporary rise in the level of the sea or a lake, which is often caused by long-lasting heavy storms. Floods can result in accidental death, disease, and property damage and crop loss. China is one of the countries damaged by rainstorm flood disasters. According to preliminary statistics of the national flood data during 1950-2006, the average flood stricken area was 9.6702 million hm2 per a year in the country, and inundated area of flood disaster was 5.4255 million hm2 with a mean hazard rate of 56.1%. Now, flood prevention has become one of most serious issues in the word. Scientific evaluation and forecast for floods are the foundation of disaster mitigation and have a heavy influence on disaster prevention function. It has always been a hotspot and difficulty in the research of scholars at home and abroad. The research about rainstorm flood disasters on human health and vulnerable populations has a major public health implication.Both the domestic and foreign research shows that direct death, injury, wound infection, dermatitis, infectious diseases, poisoning, hypothermia, respiratory system disease and mental health are flood-related health concern. Overall, the epidemiological review suggests that there is presently a weak evidence-base to assess the health impacts of flooding. Few studies have been conducted about the impact of rainstorm floods on human health, and most studies were only conducted in terms of one single flood event with a lack of a longitudinal analysis. To our knowledge, there has been no systematic research about the impact of rainstorm floods on human health. It is no clear about flood-sensitive health outcomes and the extent of impact of floods on sensitive diseases is still not known. With the development of public health, although most infectious diseases associated with floods have dropped to a lower level, the source of infection and the conditions required for transmission are still existent after floods. And infectious diseases are still a serious threat to the public health in China. Therefore, disease prevention and control is still faced with a grim situation after floods. It is of great importance on public health to study risk of infectious diseases caused by floods. In addition, it is plausible that research using a long time scale and large spatial scale data become a reality with the arrival of information age and the application of big data. Through a large number of meteorological disaster and human disease information, this study focuses on following three aspects:(1) to identify flood-sensitive infectious diseases, and determine the spectrum of infectious diseases which is associated with floods; (2) to quantify the impact of floods on sensitive infectious diseases based on time series analysis and case-crossover design; (3) to estimate attributable burden of sensitive infectious diseases due to floods based on the WHO environmental framework of comparative risk assessment (CRA).Objectives(1) The study aimed to identify flood-sensitive infectious diseases with ecological regression models.(2) The study was to establish an appropriate quantitative model to evaluate the relationship between sensitive infectious diseases and floods in the study sites based on time series analysis models and case crossover design.(3) The study aimed to examine the lagged time and the risk of floods on sensitive infectious diseases.(4) The CRA model was used to estimate burden of disease attributable to floods.MethodsBased on frequency of floods and distribution characteristics of river basin, Guangxi Zhuang autonomous region was chosen as our study area for identifying flood-sensitive infectious diseases and assessing the impact of floods on sensitive infectious diseases over a longer time scale. And northern of Anhui Province was chosen as our study area for studying on one typical serious flooding in recent years. Disease surveillance data on infectious diseases were obtained from the National Notifiable Disease Surveillance System of China information system for disease control and prevention. Flood data were collected from the Yearbooks in China and the China Meteorological Data Sharing Service System.Ecological trend study was performed to identify flood-sensitive infectious diseases. Firstly,39 kinds of notified infectious diseases were preliminary identified according to mechanism of transmission and epidemic characteristics of infectious diseases in the study area. The infectious diseases which is not associated with floods were excluded. Then, a descriptive analysis was performed to describe distribution of infectious diseases such as age, time and place. The diseases were not incorporated in the next analysis, because the number of these diseases during the study period was too small to assess the effect of floods, and there was more of an uncertainty, for them the results may be instability. The exposure periods and reference periods were selected according to floods in the study sites. The primary sensitive diseases were selected through comparing the morbidity of infectious diseases between exposure and reference periods. With adjustment for potential confounding factors, multivariable regression models were performed to evaluate the relationship between each infectious disease and floods. The diseases with statistically significance in the models were assessed the reliability of results by theories of epidemiology. And we determined the spectrum of infectious diseases which is associated with floods.Time series analysis and case-crossover design were performed to examine the relationship between key sensitive infectious diseases and floods. Firstly, we examined the association between key sensitive infectious diseases and floods from a long time scale. A generalized additive mixed (GAM) model was adopted to carry out the risk assessment on acute hemorrhagic conjunctivitis (AHC) caused by floods. Panel data model was conducted to quantify the association between monthly attack rate of tuberculosis and monthly flood days. Then, the study was carried out to assess the impact of the typical floods on infectious diarrhea and malaria. A time-stratified case-crossover analysis was firstly conducted to examine the relationship between daily cases of infectious diarrhea and the 2007 floods in Fuyang and Bozhou of Anhui Province. A 1:3 symmetric bidirectional case-crossover study was performed to evaluate the relationship between daily number of cases of malaria and flooding and waterlogging in the 2007 Huaihe River floods.The attributable burden of disease caused by floods was estimated based on the environmental framework of CRA. After fitting the lags, we collected cases of AHC, infectious diarrhea and malaria during the hazard period of the floods. The method to estimate the years lived with disability (YLDs) as recommended by the WHO was used to assess the disease burden of these three diseases. The potential impact fractions (PIFs) of AHC, infectious diarrhea and malaria were estimated based on the environmental framework of CRA developed by the WHO. The method of estimating attributable YLDs as recommended by the World Health Organization (WHO) was used to calculate burden of diseases during exposure effect-period of floods. The YLDs for the population were multiplied by PIFs to calculate the fraction of AHC, infectious diarrhea and malaria attributable to floods for the study population.Results(1) Results from Wilcoxon rank test showed that bacillary dysentery, amebic dysentery, other infectious diarrhea, AHC, influenza A (H1N1), tuberculosis, pertussis, influenza, measles, hemorrhagic fever with renal syndrome (HFRS), rabies, epidemic encephalitis B (EEB), anthrax, leptospirosis and P. falciparum malaria were maybe associated with floods. The strongest effects were observed at 1 ten-day for bacillary dysentery,2 ten-day for amebic dysentery,6 ten-day for other infectious diarrhea,0 ten-day for AHC,7 ten-day for influenza A(H1N1),9 ten-day for tuberculosis,0 month or 8 ten-day for pertussis,0 ten-day for influenza, 0 month or 0 ten-day for measles,8 ten-day for HFRS,9 ten-day for rabies,0 ten-day or 0 month for EEB,12 ten-day for anthrax,5 ten-day for leptospirosis and 1 month for P. falciparum malaria, respectively.(2) Multivariable ecological regression models showed sensitive infectious diseases from floods were bacillary dysentery (OR=1.228,95% CI:1.072-1.500), AHC (OR=3.230,95% CI: 1.976-5.280), influenza A (HiNi) (OR=1.808,95% CI:1.721-1.901), tuberculosis (OR=1.200, 95% CI:1.036-1.391), influenza (OR=2.614,95% CI:1.476-4.629), HFRS (OR=1.284,95% CI:1.104-1.493), EEB (OR=2.232,95% CI:1.302-3.827 or OR=2.334,95% CI:1.119-4.865), leptospirosis (OR=1.138,95% CI:1.075-1.205), and P. falciparum malaria (OR=3.476,95% CI:1.497-8.075).(3) The results from Spearman’s correlation analysis indicated that the strongest correlation between monthly flood days and tuberculosis were observed at 3 months (rs=0.165, p<0.05). From other lagged effects analysis, the strongest effect was shown with 0 ten-day lag for AHC (RR=1.026,p=0.014), the strongest effect was shown with a 2-day lag in Fuyang and 5 ten-day lag in Bozhou for infectious diarrhea, and the strongest effect of malaria was shown with a 25-day lag for flooding and a 7-day lag for waterlogging.(4) Multivariable GAM analysis showed that the risk of floods on the morbidity of AHC was 2.048 (95% CI:1.075-3.903) or 2.358 (95% CI:1.229-4.625), and the risk of flood days in one ten-day was 1.091 (95% CI:1.086-1.095). Multivariable panel data model showed that monthly flood days were positively correlated to the monthly attack rate of tuberculosis [incident rate ratio (IRR)=1.395,95% CI:1.244-1.565; or IRR=1.401,95% CI:1.249-1.571]. The time-stratified case-crossover study indicated that floods were significantly associated with an increased risk of the number cases of infectious diarrhea (OR=3.175,95% CI:1.126-8.954 in Fuyang; OR=6.754,95%CI:1.954-23.344 in Bozhou). The 1:3 symmetric bidirectional case-crossover study showed that an increased risk of malaria was significantly associated with flooding alone [adjusted hazard ratio (AHR)=1.467,95% CI=1.257-1.713], waterlogging alone (AHR=1.879,95%CI=1.696-2.121), and flooding and waterlogging together (AHR=2.631,95% CI=2.341-2.956).(5) PIFs of the study population exposed to floods were 0.2033/0.2485 for AHC and 0.807 for other infectious diarrhea. PIFs of the study population for malaria exposed to flooding alone, waterlogging alone, and flooding and waterlogging together were 31.8%,47.3%, and 62.0%, respectively.(6) Attributable YLD per 1000 of AHC resulting from floods was 0.0407 (95% CI: 0.0004-0.0827) or 0.0497 (95% CI:0.0106-0.0938). Attributable YLD per 1000 of infectious diarrhea resulting from the floods was 0.0081 in Fuyang and 0.0209 in Bozhou. YLDs per 1000 of malaria attributable to flooding alone, waterlogging alone and flooding and waterlogging together were 0.009 per day,0.019 per day and 0.022 per day, respectively.Conclusions(1) The spectrum of infectious diseases which is associated with floods were bacillary dysentery, AHC, influenza A (H1N1), tuberculosis, influenza, HFRS, EEB, leptospirosis and malaria (especially P. falciparum) in Guangxi.(2) Floods have significantly increased the risk of AHC in the study areas. Particular vulnerable groups-children and adolescents should be paid more attention.(3) Floods play an important role in the transmission of tuberculosis. Monthly flood days with a 3-month lag are correlation to the morbidity of tuberculosis. With increase in monthly flood days, people run an increased risk of developing tuberculosis.(4) Our findings confirm that floods have significantly increased the risks of infectious diarrhea in the study areas. In addition, prolonged moderate flood may cause more burdens of infectious diarrheas than severe flood with a shorter duration. More attention should be paid to particular vulnerable groups, including younger children and elderly, in developing public health preparation and intervention programs.(5) Flooding and waterlogging can lead to higher burden of malaria in the study area. In addition, risk of malaria caused by both flooding and waterlogging is greater than their individual risk alone. Particular vulnerable groups, including males, older people and children, should be paid more attention in developing strategies to prevent and reduce the health impact of flooding and waterlogging.Innovation(1) The study proposes the spectrum of sensitive infectious diseases which is associated with floods. Increased risk of some infectious diseases have been noted after floods in some studies. However, it is no clear about flood-sensitive infectious diseases in China. This was first time that the study identified flood-sensitive infectious diseases. The results could help determine the spectrum of infectious diseases which is associated with floods in Guangxi.(2) According to the characteristics of floods-health, the strength of the association between sensitive infectious diseases and floods was assessed from a long time sequence in multiple regions. GAM was conducted to carry out the risk assessment on AHC caused by floods, and the results indicated that floods could increase the risk of AHC. It was first time that panel data model was conducted to carry out the risk assessment on tuberculosis caused by floods. And the findings confirm that floods play an important role in the transmission of tuberculosis.(3) We adopted a comprehensive measurement-YLDs, which can assist in evidence-based allocation of limited health resources, to estimate burden of disease. This study has, for the first time, quantified the association between floods and infectious diarrhea in northwest of Anhui Province, China. The attributable burden of disease due to AHC caused by floods was estimated from a long time scale. The study confirms that epidemic of insect-borne infectious diseases have close relationship with agriculture meteorological disasters-waterlogging. And the impact of flooding and waterlogging together for malaria showed synergistic effect. |
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