Extreme precipitation and emergency room visits for influenza in Massachusetts: a case-crossover analysis

Presentation Rates for Acute Pharyngitis in the Emergency Room Are Influenced by Extreme Weather Events

OBJECTIVE

Extreme weather events are becoming more prevalent with the increasing pace of climate change. These events negatively impact human health and put considerable strain on health care resources, including emergency departments. Within otolaryngology, acute pharyngitis is a common reason for emergency room visits (ERV). Therefore, we aimed to investigate the impact of extreme meteorological conditions on ERV rates related to acute pharyngitis.

STUDY DESIGN

Retrospective time-series study.

SETTING

ERVs related to acute pharyngitis (n = 1511) were identified at a tertiary care hospital in Vienna, Austria, between 2015 and 2018.

METHODS

The effects of single-day and prolonged (3-day) extreme weather events on ERVs were analyzed using a distributed lag nonlinear model. Relative risk (RR) and cumulative relative risk (cRR) were calculated over a lag period of 14 days. RR refers to the risk for pharyngitis-related ERV at extreme conditions (1st, 5th, 95th, or 99th percentile) compared to the risk at median conditions.

RESULTS

Same-day RR (lag0) was elevated more than 3-fold after prolonged extremely low mean temperatures (P = .028). Furthermore, same-day RR after single-day and prolonged extremely high relative humidity was elevated by 51% (P = .024) and 46% (P = .036), respectively. Significant delayed effects on cRR were observed for extreme mean temperatures, relative humidity, and mean wind speeds within 8 days and for extreme atmospheric pressure within 14 days.

CONCLUSION

Extreme weather events impact ERV rates for acute pharyngitis. Extremely low temperatures, high relative humidity, high atmospheric pressure, and low and high wind speeds were risk-promoting factors.

Planetary health: an imperative for pediatric radiology

The global temperature has been increasing resulting in climate change. This negatively impacts planetary health that disproportionately affects the most vulnerable among us, especially children. Extreme weather events, such as hurricanes, tornadoes, wildfires, flooding, and heatwaves, are becoming more frequent and severe, posing a significant threat to our patients' health, safety, and security. Concurrently, shifts in environmental exposures, including air pollution, allergens, pathogenic vectors, and microplastics, further exacerbate the risks faced by children. In this paper, we provide an overview of pediatric illnesses that are becoming more prevalent and severe because of extreme weather events, global temperature increases, and shifts in environmental exposures. As members of pediatric health care teams, it is crucial for pediatric radiologists to be knowledgeable about the impacts of climate change on our patients, and continue to advocate for safe, healthier environments for our patients.

Joint extremes in precipitation and infectious disease in the USA: A bivariate POT study

Mounting heavy precipitation events (HPEs) caused by the climate change have drawn wide attention. Increased incidences of infectious diseases are known as the common following health impact, while little has been studied about the extremal relationship in between. Therefore, this study aims to investigate the joint extremes of precipitation and infectious disease mortality rate in the USA, using publicly accessible data from the National Centers for Environmental Information and the Centers for Disease Control and Prevention. The study reveals the positive association between heavy precipitations and infectious diseases with slight national and regional differences using multivariate Peaks-Over-Threshold modelling. The strength of extremal dependence is measured by the extreme parameter α from a logistic dependence model in multivariate extreme value theory. The Midwestern USA shows an excessive impact of HPEs on infectious disease mortality (α = 0.7524 ), while the other regions show similar extremal dependence strength with the national one (α values all approximate 0.77). The study also discovered spatial disparities in the extremal dependences for five sub-categories of infectious diseases in each census region, among which mycoses show the strongest extremal dependence with precipitation in almost all regions. These spatial differences of extremal dependence may be attributed to geographic, social-economic factors and the self-inherited characteristics of certain diseases. The findings are expected to assist in developing strategies counteracting extreme risks resulting from weather events and health issues as well. The cutting-edge multivariate Peaks-Over-Threshold (POT) approach employed herein also shows promise for a wide range of extreme risk assessment topics.

Association of climatic variables with risk of transmission of influenza in Guangzhou, China, 2005-2021

BACKGROUND

Climatic variables constitute important extrinsic determinants of transmission and seasonality of influenza. Yet quantitative evidence of independent associations of viral transmissibility with climatic factors has thus far been scarce and little is known about the potential effects of interactions between climatic factors on transmission.

OBJECTIVE

This study aimed to examine the associations of key climatic factors with risk of influenza transmission in subtropical Guangzhou.

METHODS

Influenza epidemics were identified over a 17-year period using the moving epidemic method (MEM) from a dataset of N = 295,981 clinically- and laboratory-confirmed cases of influenza in Guangzhou. Data on eight key climatic variables were collected from China Meteorological Data Service Centre. Generalized additive model combined with the distributed lag non-linear model (DLNM) were developed to estimate the exposure-lag-response curve showing the trajectory of instantaneous reproduction number (R_t) across the distribution of each climatic variable after adjusting for depletion of susceptible, inter-epidemic effect and school holidays. The potential interaction effects of temperature, humidity and rainfall on influenza transmission were also examined.

RESULTS

Over the study period (2005-21), 21 distinct influenza epidemics with varying peak timings and durations were identified. Increasing air temperature, sunshine, absolute and relative humidity were significantly associated with lower R_t, while the associations were opposite in the case of ambient pressure, wind speed and rainfall. Rainfall, relative humidity, and ambient temperature were the top three climatic contributors to variance in transmissibility. Interaction models found that the detrimental association between high relative humidity and transmissibility was more pronounced at high temperature and rainfall.

CONCLUSION

Our findings are likely to help understand the complex role of climatic factors in influenza transmission, guiding informed climate-related mitigation and adaptation policies to reduce transmission in high density subtropical cities.

Association between extreme rainfall and acute respiratory infection among children under-5 years in sub-Saharan Africa: an analysis of Demographic and Health Survey data, 2006-2020

OBJECTIVE

Despite an increase in the number of studies examining the association between extreme weather events and infectious diseases, evidence on respiratory infection remains scarce. This study examined the association between extreme rainfall and acute respiratory infection (ARI) in children aged <5 years in sub-Saharan Africa.

SETTING

Study data were taken from recent (2006-2020) Demographic and Health Survey data sets from 33 countries in sub-Saharan Africa.

PARTICIPANTS

280 157 children aged below 5 years were included.

OUTCOME MEASURES

The proportions of ARI according to individual, household and geographical characteristics were compared using the χ² test. The association between extreme rainfall (≥90th percentile) and ARI was examined using multivariate logistic regression for 10 of 33 countries with an adequate sample size of ARI and extreme rainfall events. The model was adjusted for temperature, comorbidity and sociodemographic factors as covariates. Stratification analyses by climate zone were also performed.

RESULTS

The prevalence of ARI in children aged <5 years ranged from 1.0% to 9.1% across sub-Saharan Africa. By country, no significant association was observed between extreme rainfall and ARI, except in Nigeria (OR: 2.14, 95% CI 1.06 to 4.31). Larger effect estimates were observed in the tropical zone (OR: 1.13, 95% CI 0.69 to 1.84) than in the arid zone (OR: 0.72, 95% CI 0.17 to 2.95), although the difference was not statistically significant.

CONCLUSION

We found no association between extreme rainfall and ARI in sub-Saharan Africa. Effect estimates tended to be larger in the tropical zone where intense rainfall events regularly occur. Comprehensive studies to investigate subsequent extreme climate events, such as flooding, are warranted in the future.

Agreement in extreme precipitation exposure assessment is modified by race and social vulnerability

Epidemiologic investigations of extreme precipitation events (EPEs) often rely on observations from the nearest weather station to represent individuals' exposures, and due to structural factors that determine the siting of weather stations, levels of measurement error and misclassification bias may differ by race, class, and other measures of social vulnerability. Gridded climate datasets provide higher spatial resolution that may improve measurement error and misclassification bias. However, similarities in the ability to identify EPEs among these types of datasets have not been explored. In this study, we characterize the overall and temporal patterns of agreement among three commonly used meteorological data sources in their identification of EPEs in all census tracts and counties in the conterminous United States over the 1991-2020 U.S. Climate Normals period and evaluate the association between sociodemographic characteristics with agreement in EPE identification. Daily precipitation measurements from weather stations in the Global Historical Climatology Network (GHCN) and gridded precipitation estimates from the Parameter-elevation Relationships on Independent Slopes Model (PRISM) and the North American Land Data Assimilation System (NLDAS) were compared in their ability to identify EPEs defined as the top 1% of precipitation events or daily precipitation >1 inch. Agreement among these datasets is fair to moderate from 1991 to 2020. There are spatial and temporal differences in the levels of agreement between ground stations and gridded climate datasets in their detection of EPEs in the United States from 1991 to 2020. Spatial variation in agreement is most strongly related to a location's proximity to the nearest ground station, with areas furthest from a ground station demonstrating the lowest levels of agreement. These areas have lower socioeconomic status, a higher proportion of Native American population, and higher social vulnerability index scores. The addition of ground stations in these areas may increase agreement, and future studies intending to use these or similar data sources should be aware of the limitations, biases, and potential for differential misclassification of exposure to EPEs. Most importantly, vulnerable populations should be engaged to determine their priorities for enhanced surveillance of climate-based threats so that community-identified needs are met by any future improvements in data quality.

Association of extreme precipitation with hospitalizations for acute myocardial infarction in Beijing, China: A time-series study

Background

In the context of global climate changes, increasing extreme weather events have aroused great public concern. Limited evidence has focused on the association between extreme precipitation and hospitalizations for acute myocardial infarction (AMI). Our study aimed to examine the effect of extreme precipitation on AMI hospitalizations.

Methods

Daily AMI hospitalizations, weather variables and air pollution data in Beijing from 2013 to 2018 were obtained. We used a time-series analysis with a distributed lag model to evaluate the association of extreme precipitation (≥95th percentile of daily precipitation) with AMI hospitalizations. Subgroup analysis was conducted to identify the vulnerable subpopulations and further assessed the attributable burden.

Results

Extreme precipitation increased the risk of AMI hospitalizations with significant single-day effects from Lag 4 to Lag 11, and the maximum cumulative effects at Lag 0-14 (CRR = 1.177, 95% CI: 1.045, 1.326). Older people (≥65 years) and females were more vulnerable to extreme precipitation. The attributable fraction and numbers of extreme precipitation on AMI hospitalizations were 0.68% (95% CI: 0.20%, 1.12%) and 854 (95% CI: 244, 1,395), respectively.

Conclusion

Extreme precipitation is correlated with a higher risk of AMI hospitalizations. The elderly (≥65 years) and females are more susceptible to AMI triggered by extreme precipitation.

The effect of temperature, humidity, precipitation and cloud coverage on the risk of COVID-19 infection in temperate regions of the USA—A case-crossover study

Background

Observations based on the spread of SARS-CoV-2 early into the COVID-19 pandemic have suggested a reduced burden in tropical regions leading to the assumption of a dichotomy between cold and dry and wet and warm climates.

Objectives

Analyzing more than a whole year of COVID-19 infection data, this study intents to refine the understanding of meteorological variables (temperature, humidity, precipitation and cloud coverage) on COVID-19 transmission in settings that experience distinct seasonal changes.

Methods and findings

A time stratified case-crossover design was adopted with a conditional Poisson model in combination with a distributed lag nonlinear model to assess the short-term impact of mentioned meteorological factors on COVID-19 infections in five US study sites (New York City (NYC); Marion County, Indiana (MCI); Baltimore and Baltimore County, Maryland (BCM); Franklin County, Ohio (FCO); King County, Washington (KCW)). Higher-than-average temperatures were consistently associated with a decreased relative risk (RR) of COVID-19 infection in four study sites. At 20 degrees Celsius COVID-19 infection was associated with a relative risk of 0.35 (95%CI: 0.20–0.60) in NYC, 1.03 (95%CI:0.57–1.84) in MCI, 0.34 (95%CI: 0.20–0.57) in BCM, 0.52 (95%CI: 0.31–0.87) in FCO and 0.21 (95%CI: 0.10–0.44) in KCW. Higher-than-average humidity levels were associated with an increased relative risk of COVID-19 infection in four study sites. Relative to their respective means, at a humidity level of 15 g/kg (specific humidity) the RR was 5.83 (95%CI: 2.05–16.58) in BCM, at a humidity level of 10 g/kg the RR was 3.44 (95%CI: 1.95–6.01) in KCW.

Conclusions

The results of this study suggest opposed effects for higher-than-average temperature and humidity concerning the risk of COVID-19 infection. While a distinct seasonal pattern of COVID-19 has not yet emerged, warm and humid weather should not be generally regarded as a time of reduced risk of COVID-19 infections.

Community-level ambient fine particulate matter and seasonal influenza among children in Guangzhou, China: A Bayesian spatiotemporal analysis

BACKGROUND

Influenza is a major preventable infectious respiratory disease. However, there is little detailed long-term evidence of its associations with PM_2.5 among children. We examined the community-level associations between exposure to ambient PM_2.5 and incident influenza in Guangzhou, China.

METHODS

We used data from the city-wide influenza surveillance system collected by Guangzhou Centre for Disease Control and Prevention (GZCDC) over the period 2013 and 2019. Incident influenza was defined as daily new influenza (both clinically diagnosed and laboratory confirmed) cases as per standard diagnostic criteria. A 200-meter city-wide grid of daily ambient PM_2.5 exposure was generated using a random forest model. We developed spatiotemporal Bayesian hierarchical models to examine the community-level associations between PM_2.5 and the influenza adjusting for meteorological and socioeconomic variables and accounting for spatial autocorrelation. We also calculated community-wide influenza cases attributable to PM_2.5 levels exceeding the China Grade 1 and World Health Organization (WHO) regulatory thresholds.

RESULTS

Our study comprised N = 191,846 children from Guangzhou aged ≤19 years and diagnosed with influenza between January 1, 2013 and December 31, 2019. Each 10 μg/m³ increment in community-level PM_2.5 measured on the day of case confirmation (lag 0) and over a 6-day moving average (lag 0-5 days) was associated with higher risks of influenza (RR = 1.05, 95% CI: 1.05-1.06 for lag 0 and RR = 1.15, 95% CI: 1.14-1.16 for lag 05). We estimated that 8.10% (95%CI: 7.23%-8.57%) and 20.11% (95%CI: 17.64%-21.48%) influenza cases respectively were attributable to daily PM_2.5 exposure exceeding the China Grade I (35 μg/m³) and the WHO limits (25 μg/m³). The risks associated with PM_2.5 exposures were more pronounced among children of the age-group 10-14 compared to other age groups.

CONCLUSIONS

More targeted non-pharmaceutical interventions aimed at reducing PM_2.5 exposures at home, school and during commutes among children may constitute additional influenza prevention and control polices.

Racial Disparities in Climate Change-Related Health Effects in the United States

PURPOSE OF REVIEW

Climate change is causing warming over most parts of the USA and more extreme weather events. The health impacts of these changes are not experienced equally. We synthesize the recent evidence that climatic changes linked to global warming are having a disparate impact on the health of people of color, including children.

RECENT FINDINGS

Multiple studies of heat, extreme cold, hurricanes, flooding, and wildfires find evidence that people of color, including Black, Latinx, Native American, Pacific Islander, and Asian communities are at higher risk of climate-related health impacts than Whites, although this is not always the case. Studies of adults have found evidence of racial disparities related to climatic changes with respect to mortality, respiratory and cardiovascular disease, mental health, and heat-related illness. Children are particularly vulnerable to the health impacts of climate change, and infants and children of color have experienced adverse perinatal outcomes, occupational heat stress, and increases in emergency department visits associated with extreme weather. The evidence strongly suggests climate change is an environmental injustice that is likely to exacerbate existing racial disparities across a broad range of health outcomes.

Projecting the Impacts of a Changing Climate: Tropical Cyclones and Flooding

PURPOSE OF REVIEW

There is clear evidence that the earth's climate is changing, largely from anthropogenic causes. Flooding and tropical cyclones have clear impacts on human health in the United States at present, and projections of their health impacts in the future will help inform climate policy, yet to date there have been few quantitative climate health impact projections.

RECENT FINDINGS

Despite a wealth of studies characterizing health impacts of floods and tropical cyclones, many are better suited for qualitative, rather than quantitative, projections of climate change health impacts. However, a growing number have features that will facilitate their use in quantitative projections, features we highlight here. Further, while it can be difficult to project how exposures to flood and tropical cyclone hazards will change in the future, climate science continues to advance in its capabilities to capture changes in these exposures, including capturing regional variation. Developments in climate epidemiology and climate science are opening new possibilities in projecting the health impacts of floods and tropical cyclones under a changing climate.

Effects of extreme precipitation on hospitalization risk and disease burden of schizophrenia in urban and rural Lu'an, China, from 2010 to 2019

With the increasing frequency of extreme events caused by global climate change, the association between extreme precipitation (EP) and disease has aroused concern currently. However, no study has examined the relationship between EP and schizophrenia. Our study aimed to explore the relationship between EP and schizophrenia, and to further examine the difference between urban and rural areas. This study used quasi-Poisson generalized linear regression model combined with distributed lag non-linear model (DLNM) to estimate the association between EP (≥ 95th percentile) and hospitalization for schizophrenia from 2010 to 2019 in the city of Lu'an, China. EP could significantly increase the risk of hospitalization for schizophrenia. The effect firstly appeared at lag1 [relative risk (RR): 1.056, 95% confidence interval (95%CI): 1.003-1.110] and continued until lag17 (RR: 1.039, 95%CI: 1.004-1.075). Our research showed that EP had a significant effect on the hospitalization for schizophrenia in both urban and rural areas, and no significant difference was found (p>0.05). EP exerted more acute effects on schizophrenia living in rural areas than those in urban areas in the cold season. Further studies on the burden of schizophrenia found that patients who are male, aged ≤ 39 years or less, and living in urban areas are a priority for future warnings. We should pay more attention to the impact of EP on burden of schizophrenia, especially during the cold season, targeting those vulnerable groups, thereby implementing more accurate and timely preventive measures.

Extreme Precipitation Events and Infectious Disease Risk: A Scoping Review and Framework for Infectious Respiratory Viruses

Extreme precipitation events (EPE) change the natural and built environments and alter human behavior in ways that facilitate infectious disease transmission. EPEs are expected with high confidence to increase in frequency and are thus of great public health importance. This scoping review seeks to summarize the mechanisms and severity of impacts of EPEs on infectious diseases, to provide a conceptual framework for the influence of EPEs on infectious respiratory diseases, and to define areas of future study currently lacking in this field. The effects of EPEs are well-studied with respect to enteric, vector-borne, and allergic illness where they are shown to moderately increase risk of illness, but not well-understood in relation to infectious respiratory illness. We propose a framework for a similar influence of EPEs on infectious respiratory viruses through several plausible pathways: decreased UV radiation, increased ambient relative humidity, and changes to human behavior (increased time indoors and use of heating and cooling systems). However, limited work has evaluated meteorologic risk factors for infectious respiratory diseases. Future research is needed to evaluate the effects of EPEs on infectious respiratory diseases using individual-level case surveillance, fine spatial scales, and lag periods suited to the incubation periods of the disease under study, as well as a full characterization of susceptible, vulnerable, and sensitive population characteristics.

Seasonality of Non-SARS, Non-MERS Coronaviruses and the Impact of Meteorological Factors

Background: Seasonality is a characteristic of some respiratory viruses. The aim of our study was to evaluate the seasonality and the potential effects of different meteorological factors on the detection rate of the non-SARS coronavirus detection by PCR. Methods: We performed a retrospective analysis of 12,763 respiratory tract sample results (288 positive and 12,475 negative) for non-SARS, non-MERS coronaviruses (NL63, 229E, OC43, HKU1). The effect of seven single weather factors on the coronavirus detection rate was fitted in a logistic regression model with and without adjusting for other weather factors. Results: Coronavirus infections followed a seasonal pattern peaking from December to March and plunged from July to September. The seasonal effect was less pronounced in immunosuppressed patients compared to immunocompetent patients. Different automatic variable selection processes agreed on selecting the predictors temperature, relative humidity, cloud cover and precipitation as remaining predictors in the multivariable logistic regression model, including all weather factors, with low ambient temperature, low relative humidity, high cloud cover and high precipitation being linked to increased coronavirus detection rates. Conclusions: Coronavirus infections followed a seasonal pattern, which was more pronounced in immunocompetent patients compared to immunosuppressed patients. Several meteorological factors were associated with the coronavirus detection rate. However, when mutually adjusting for all weather factors, only temperature, relative humidity, precipitation and cloud cover contributed independently to predicting the coronavirus detection rate.

Climate Change and Childhood Respiratory Health: A Call to Action for Paediatricians

Climate change (CC) is one of the main contributors to health emergencies worldwide. CC appears to be closely interrelated with air pollution, as some pollutants like carbon dioxide (CO2), nitrogen oxides (NOx) and black carbon are naturally occurring greenhouse gases. Air pollution may enhance the allergenicity of some plants and, also, has an adverse effect on respiratory health. Children are a uniquely vulnerable group that suffers disproportionately from CC burden. The increasing global warming related to CC has a big impact on plants' lifecycles, with earlier and longer pollen seasons, as well as higher pollen production, putting children affected by asthma and allergic rhinitis at risk for exacerbations. Extreme weather events may play a role too, not only in the exacerbations of allergic respiratory diseases but, also, in favouring respiratory infections. Even though paediatricians are already seeing the impacts of CC on their patients, their knowledge about CC-related health outcomes with specific regards to children's respiratory health is incomplete. This advocates for paediatricians' increased awareness and a better understanding of the CC impact on children's respiratory health. Having a special responsibility for children, paediatricians should actively be involved in policies aimed to protect the next generation from CC-related adverse health effects. Hence, there is an urgent need for them to take action and successfully educate families about CC issues. This paper aims at reviewing the evidence of CC-related environmental factors such as temperature, humidity, rainfall and extreme events on respiratory allergic diseases and respiratory infections in children and proposing specific actionable items for paediatricians to deal with CC-related health issues in their clinical practice.

Human respiratory syncytial virus and influenza seasonality patterns-Early findings from the WHO global respiratory syncytial virus surveillance

Background

Human respiratory syncytial virus (RSV) causes illnesses among all age groups and presents a burden to healthcare services. To better understand the epidemiology and seasonality of RSV in different geographical areas, the World Health Organization (WHO) coordinated a pilot initiative to access the feasibility of establishing RSV surveillance using the existing Global Influenza Surveillance and Response System (GISRS) platform.

Objectives

To describe and compare RSV and influenza seasonality in countries in the northern andsouthern temperate, and tropics during the period January 2017 to April 2019.

Methods

Fourteen countries in six WHO regions participating in the GISRS were invited for the pilot. Hospitalized patients presenting with severe acute respiratory illness (SARI), SARI without fever and outpatients presenting with acute respiratory illness (ARI) were enrolled from January 2017 to April 2019. The expected minimum sample size was 20 samples per week, year‐round, per country. Real‐time RT‐PCR was used to detect RSV and influenza viruses. Results were uploaded to the WHO FluMart platform.

Results

Annual seasonality of RSV was observed in all countries, which overlapped to a large extent with the influenza activity. In countries, in temperate regions RSV peaked in the autumn/winter months. In Egypt, a subtropical country, RSV activity peaked in the cooler season. In the tropical regions, RSV peaked during the rainy seasons.

Conclusion

Early findings from the WHO RSV surveillance pilot based on the GISRS suggest annual seasonal patterns for of RSV circulation that overlap with influenza. RSV surveillance needs to be continued for several more seasons to establish seasonality patterns to inform prevention and control strategies.