Association between flood and the morbidity of bacillary dysentery in Zibo City, China: a symmetric bidirectional case-crossover study

Climate Change and Respiratory Diseases: Relationship between SARS and Climatic Parameters and Impact of Climate Change on the Geographical Distribution of SARS in Iran

Climate change affects human health, and severe acute respiratory syndrome (SARS) incidence is one of the health impacts of climate change. This study is a retrospective cohort study. Data have been collected from the Iranian Ministry of Health and Medical Education between 17 February 2016 and17 February 2018. The Neural Network Model has been used to predict SARS infection. Based on the results of the multivariate Poisson regression and the analysis of the coexistence of the variables, the minimum daily temperature was positively associated with the risk of SARS in men and women. The risk of SARS has increased in women and men with increasing daily rainfall. According to the result, by changes in bioclimatic parameters, the number of SARS patients will be increased in cities of Iran. Our study has shown a significant relationship between SARS and the climatic variables by the type of climate and gender. The estimates suggest that hospital admissions for climate-related respiratory diseases in Iran will increase by 36% from 2020 to 2050. This study demonstrates one of the health impacts of climate change. Policymakers can control the risks of climate change by mitigation and adaptation strategists.

Shigellosis seasonality and transmission characteristics in different areas of China: A modelling study

Objective

In China, the burden of shigellosis is unevenly distributed, notably across various ages and geographical areas. Shigellosis temporal trends appear to be seasonal. We should clarify seasonal warnings and regional transmission patterns.

Method

This study adopted a Logistic model to assess the seasonality and a dynamics model to compare the transmission in different areas. The next-generation matrix was used to calculate the effective reproduction number (R eff) to quantify the transmissibility.

Results

In China, the rate of shigellosis fell from 35.12 cases per 100,000 people in 2005 to 7.85 cases per 100,000 people in 2017, peaking in June and August. After simulation by the Logistic model, the 'peak time' is mainly concentrated from mid-June to mid-July. China's 'early warning time' is primarily focused on from April to May. We predict the 'peak time' of shigellosis is the 6.30th month and the 'early warning time' is 3.87th month in 2021. According to the dynamics model results, the water/food transfer pathway has been mostly blocked off. The transmissibility of different regions varies greatly, such as the mean R eff of Longde County (3.76) is higher than Xiamen City (3.15), higher than Chuxiong City (2.52), and higher than Yichang City (1.70).

Conclusion

The 'early warning time' for shigellosis in China is from April to May every year, and it may continue to advance in the future, such as the early warning time in 2021 is in mid-March. Furthermore, we should focus on preventing and controlling the person-to-person route of shigellosis and stratified deploy prevention and control measures according to the regional transmission.

Association between floods and the risk of dysentery in China: a meta-analysis

The association between floods and the risk of dysentery remain controversial. Therefore, we performed a meta-analysis to clarify this relationship. A literature search was performed in PubMed, Web of science, and Embase for relevant articles published up to November 2019. Random-effects model was used to pool relative risks with 95% confidence intervals. The sensitivity analysis was carried out to evaluate the stability of the results. Publication bias was estimated using Egger's test. Eleven studies from 10 articles evaluated the association between floods and the risk of dysentery in China. The pooled RR (95% CI) of dysentery for the flooded time versus non-flooded period was 1.48 (95% CI: 1.14-1.91). Significant association was found in subgroup analysis stratified by dysentery styles [dysentery: 1.61 (95% CI: 1.34-1.93) and bacillary dysentery: 1.46 (95% CI: 1.06-2.01)]. The pooled RR (95%CI) of sensitivity analysis for dysentery was 1.26 (95% CI: 1.05-1.52). No significant publication bias was found in our meta-analysis. This meta-analysis confirms that floods have significantly increased the risk of dysentery in China. Our findings will provide more evidence to reduce negative health outcomes of floods in China.

Associations between floods and bacillary dysentery cases in main urban areas of Chongqing, China, 2005-2016: a retrospective study

BACKGROUND

Understanding the association between floods and bacillary dysentery (BD) incidence is necessary for us to assess the health risk of extreme weather events. This study aims at exploring the association between floods and daily bacillary dysentery cases in main urban areas of Chongqing between 2005 and 2016 as well as evaluating the attributable risk from floods.

METHODS

The association between floods and daily bacillary dysentery cases was evaluated by using distributed lag non-linear model, controlling for meteorological factors, long-term trend, seasonality, and day of week. The fraction and number of bacillary dysentery cases attributable to floods was calculated. Subgroup analyses were conducted to explore the association across age, gender, and occupation.

RESULTS

After controlling the impact of temperature, precipitation, relative humidity, long-term trend, and seasonality, a significant lag effect of floods on bacillary dysentery cases was found at 0-day, 3-day, and 4-day lag, and the cumulative relative risk (CRR) over a 7-lag day period was 1.393 (95%CI 1.216-1.596). Male had higher risk than female. People under 5 years old and people aged 15-64 years old had significantly higher risk. Students, workers, and children had significantly higher risk. During the study period, based on 7-lag days, the attributable fraction of bacillary dysentery cases due to floods was 1.10% and the attributable number was 497 persons.

CONCLUSIONS

This study confirms that floods can increase the risk of bacillary dysentery incidence in main urban areas of Chongqing within an accurate time scale, the risk of bacillary dysentery caused by floods is still serious. The key population includes male, people under 5 years old, students, workers, and children. Considering the lag effect of floods on bacillary dysentery, the government and public health emergency departments should advance to the emergency health response in order to minimize the potential risk of floods on public.

Impact of climate change on dysentery: Scientific evidences, uncertainty, modeling and projections

Dysentery is water-borne and food-borne infectious disease and its incidence is sensitive to climate change. Although the impact of climate change on dysentery is being studied in specific areas, a systematic review is lacking. We searched the worldwide literature using three sets of keywords and six databases. We identified and selected 98 studies during 1866-2019 and reviewed the relevant findings. Climate change, including long-term variations in factors, such as temperature, precipitation, and humidity, and short-term variations in extreme weather events, such as floods and drought, mostly had a harmful impact on dysentery incidence. However, some uncertainty over the exact effects of climate factors exists, specifically in the different indexes for the same climate factor, various determinant indexes for different dysentery burdens, and divergent effects for different population groups. These complicate the accurate quantification of such impacts. We generalized two types of methods: sensitivity analysis, used to detect the sensitivity of dysentery to climate change, including Pearson's and Spearman's correlations; and mathematical models, which quantify the impact of climate on dysentery, and include models that examine the associations (including negative binomial regression models) and quantify correlations (including single generalized additive models and mixed models). Projection studies mostly predict disease risks, and some predict disease incidence based on climate models under RCP 4.5. Since some geographic heterogeneity exists in the climate-dysentery relationship, modeling and projection of dysentery incidence on a national or global scale remain challenging. The reviewed results have implications for the present and future. Current research should be extended to select appropriate and robust climate-dysentery models, reasonable disease burden measure, and appropriate climate models and scenarios. We recommend future studies focus on qualitative investigation of the mechanism involved in the impact of climate on dysentery, and accurate projection of dysentery incidence, aided by advancing accuracy of extreme weather forecasting.

Association between rainfall and readmissions of rheumatoid arthritis patients: a time-stratified case-crossover analysis

It has been reported that local weather is associated with the symptoms of joint pain in patients with rheumatoid arthritis (RA), and many people believe their pain becomes worse when facing rainy days. However, limited studies explored the effects of weather on RA patients' healthcare-seeking behavior. Our study aimed to investigate the relationship between rainfall and readmission behavior of patients with RA in Hefei, China, based on hospitalization data from the First Affiliated Hospital of Anhui University of Chinese Medicine from May 2012 to June 2016 and weather data from National Meteorological Information Center during the same study period. Using a time-stratified case-crossover study design and conditional logistic regression, we found a negative association between current day rainfall and readmission (unadjusted: OR = 0.82, p < 0.05; adjusted: OR = 0.83, p < 0.1), which is contrary to our common belief. In lagged models, we observed that rainfall was significantly and positively associated with readmissions at lag 6 days (unadjusted: OR = 1.12, p < 0.1; adjusted: OR = 1.17, p < 0.05) and lag 7 days (unadjusted: OR = 1.13, p < 0.05; adjusted: OR = 1.21, p < 0.01). Additionally, stratified analyses showed the unanticipated finding was only statistically significant for younger patients (< 65 years) and females. Our study adds new evidence that the association between the healthcare-seeking behavior of patients with RA and local rainfall may be different, compared with the positive relationship between symptoms of joint pain and rainfall.

Exploring the Relevance of Green Space and Epidemic Diseases Based on Panel Data in China from 2007 to 2016

Urban green space has been proven effective in improving public health in the contemporary background of planetary urbanization. There is a growing body of literature investigating the relationship between non-communicable diseases (NCDs) and green space, whereas seldom has the correlation been explored between green space and epidemics, such as dysentery, tuberculosis, and malaria, which still threaten the worldwide situation of public health. Meanwhile, most studies explored healthy issues with the general green space, public green space, and green space coverage, respectively, among which the different relevance has been rarely explored. This study aimed to examine and compare the relevance between these three kinds of green space and incidences of the three types of epidemic diseases based on the Panel Data Model (PDM) with the time series data of 31 Chinese provinces from 2007 to 2016. The results indicated that there exists different, or even opposite, relevance between various kinds of green space and epidemic diseases, which might be associated with the process of urban sprawl in rapid urbanization in China. This paper provides a reference for re-thinking the indices of green space in building healthier and greener cities.

Health impact of climate change in cities of middle-income countries: the case of China

BACKGROUND

This review examines the human health impact of climate change in China. Through reviewing available research findings under four major climate change phenomena, namely extreme temperature, altered rainfall pattern, rise of sea level and extreme weather events, relevant implications for other middle-income population with similar contexts will be synthesized.

SOURCES OF DATA

Sources of data included bilingual peer-reviewed articles published between 2000 and 2018 in PubMed, Google Scholar and China Academic Journals Full-text Database.

AREAS OF AGREEMENT

The impact of temperature on mortality outcomes was the most extensively studied, with the strongest cause-specific mortality risks between temperature and cardiovascular and respiratory mortality. The geographical focuses of the studies indicated variations in health risks and impacts of different climate change phenomena across the country.

AREAS OF CONTROVERSY

While rainfall-related studies predominantly focus on its impact on infectious and vector-borne diseases, consistent associations were not often found.

GROWING POINTS

Mental health outcomes of climate change had been gaining increasing attention, particularly in the context of extreme weather events. The number of projection studies on the long-term impact had been growing.

AREAS TIMELY FOR DEVELOPING RESEARCH

The lack of studies on the health implications of rising sea levels and on comorbidity and injury outcomes warrants immediate attention. Evidence is needed to understand health impacts on vulnerable populations living in growing urbanized cities and urban enclaves, in particular migrant workers. Location-specific climate-health outcome thresholds (such as temperature-mortality threshold) will be needed to support evidence-based clinical management plans and health impact mitigation strategies to protect vulnerable communities.

The impact of the 2016 flood event in Anhui Province, China on infectious diarrhea disease: An interrupted time-series study

Climate change may bring more frequent and severe floods which will heighten public health problems, including an increased risk of infectious diarrhea in susceptible populations. Affected by heavy rainfall and an El Niño event, a destructive flood occurred in Anhui province, China on 18th June 2016. This study investigates the impact of this severe flood on infectious diarrhea at both city-level and provincial level, and further to identify modifying factor. We obtained information on infectious diarrheal cases during 2013-2017 from the National Disease Surveillance System. An interrupted time-series design was used to estimate effects of the flood event on diarrhea in 16 cities. Then we applied a meta-analysis to estimate the area-level pooled effects of the flood in both flooded areas and non-flooded areas. Finally, a meta-regression was applied to determine whether proximity to flood was a predictor of city-level risks. Stratified analyses by gender and age group were also conducted for flooded areas. A significant increase in infectious diarrhea risk (RR = 1.11, 95% CI: 1.01, 1.23) after the flood event was found in flooded area with variation in risks across cities, while there was no increase in non-flooded areas. Diarrheal risks post-flood was progressively higher in cities with greater proximity to the Yangtze River. Children aged 5-14 were at highest risk of diarrhea post-flood in the flooded areas. Our study provides strong evidence that the 2016 severe flood significantly increased infectious diarrheal risk in exposed populations. Local public health agencies are advised to develop intervention programs to prevent and control infectious diarrhea risk when a major flood occurs, especially in areas close to water bodies and among vulnerable populations.

Climate Change-Related Water Disasters' Impact on Population Health

PURPOSE

Rising global temperatures have resulted in an increased frequency and severity of cyclones, hurricanes, and flooding in many parts of the world. These climate change-related water disasters (CCRWDs) have a devastating impact on communities and the health of residents. Clinicians and policymakers require a substantive body of evidence on which to base planning, prevention, and disaster response to these events. The purpose of this study was to conduct a systematic review of the literature concerning the impact of CCRWDs on public health in order to identify factors in these events that are amenable to preparedness and mitigation. Ultimately, this evidence could be used by nurses to advocate for greater preparedness initiatives and inform national and international disaster policy.

DESIGN AND METHODS

A systematic literature review of publications identified through a comprehensive search of five relevant databases (PubMed, Cumulative Index to Nursing and Allied Health Literature [CINAHL], Embase, Scopus, and Web of Science) was conducted using a modified Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach in January 2017 to describe major themes and associated factors of the impact of CCRWDs on population health.

FINDINGS

Three major themes emerged: environmental disruption resulting in exposure to toxins, population susceptibility, and health systems infrastructure (failure to plan-prepare-mitigate, inadequate response, and lack of infrastructure). Direct health impact was characterized by four major categories: weather-related morbidity and mortality, waterborne diseases/water-related illness, vector-borne and zoonotic diseases, and psychiatric/mental health effects. Scope and duration of the event are factors that exacerbate the impact of CCRWDs. Discussion of specific factors amenable to mitigation was limited. Flooding as an event was overrepresented in this analysis (60%), and the majority of the research reviewed was conducted in high-income or upper middle-/high-income countries (62%), despite the fact that low-income countries bear a disproportionate share of the burden on morbidity and mortality from CCRWDs.

CONCLUSIONS

Empirical evidence related to CCRWDs is predominately descriptive in nature, characterizing the cascade of climatic shifts leading to major environmental disruption and exposure to toxins, and their resultant morbidity and mortality. There is inadequate representation of research exploring potentially modifiable factors associated with CCRWDs and their impact on population health. This review lays the foundation for a wide array of further areas of analysis to explore the negative health impacts of CCRWDs and for nurses to take a leadership role in identifying and advocating for evidence-based policies to plan, prevent, or mitigate these effects.

CLINICAL RELEVANCE

Nurses comprise the largest global healthcare workforce and are in a position to advocate for disaster preparedness for CCRWDs, develop more robust environmental health policies, and work towards mitigating exposure to environmental toxins that may threaten human health.

Urban air pollution and meteorological factors affect emergency department visits of elderly patients with chronic obstructive pulmonary disease in Taiwan

Both air pollution and meteorological factors in metropolitan areas increased emergency department (ED) visits from people with chronic obstructive pulmonary disease (COPD). Few studies investigated the associations between air pollution, meteorological factors, and COPD-related health disorders in Asian countries. This study aimed to investigate the relationship between the environmental factors and COPD-associated ED visits of susceptible elderly population in the largest Taiwanese metropolitan area (Taipei area, including Taipei city and New Taipei city) between 2000 and 2013. Data of air pollutant concentrations (PM₁₀, PM_2.5, O₃, SO₂, NO₂ and CO), meteorological factors (daily temperature, relative humidity and air pressure), and daily COPD-associated ED visits were collected from Taiwan Environmental Protection Administration air monitoring stations, Central Weather Bureau stations, and the Taiwan National Health Insurance database in Taipei area. We used a case-crossover study design and conditional logistic regression models with odds ratios (ORs), and 95% confidence intervals (CIs) for evaluating the associations between the environmental factors and COPD-associated ED visits. Analyses showed that PM_2.5, O₃, and SO₂ had significantly greater lag effects (the lag was 4 days for PM_2.5, and 5 days for O₃ and SO₂) on COPD-associated ED visits of the elderly population (65-79 years old). In warmer days, a significantly greater effect on elderly COPD-associated ED visits was estimated for PM_2.5 with coexistence of O₃. Additionally, either O₃ or SO₂ combined with other air pollutants increased the risk of elderly COPD-associated ED visits in the days of high relative humidity and air pressure difference, respectively. This study showed that joint effect of urban air pollution and meteorological factors contributed to the COPD-associated ED visits of the susceptible elderly population in the largest metropolitan area in Taiwan. Government authorities should review existing air pollution policies, and strengthen health education propaganda to ensure the health of the susceptible elderly population.