Incidence and seasonality of Kawasaki disease in children in the Philippines, and its association with ambient air temperature.

Background: Despite an unknown cause, Kawasaki disease (KD) is currently the primary leading cause of acquired heart disease in developed countries in children and has been increasing in recent years. Research efforts have explored environmental factors related to KD, but they are still unclear especially in the tropics. We aimed to describe the incidence of KD in children, assess its seasonality, and determine its association with ambient air temperature in the National Capital Region (NCR), Philippines from January 2009 to December 2019. Methods: Monthly number of KD cases from the Philippine Pediatric Society (PPS) disease registry was collected to determine the incidence of KD. A generalized linear model (GLM) with quasi-Poisson regression was utilized to assess the seasonality of KD and determine its association with ambient air temperature after adjusting for the relevant confounders. Results: The majority of KD cases (68.52%) occurred in children less than five years old, with incidence rates ranging from 14.98 to 23.20 cases per 100,000 population, and a male-to-female ratio of 1.43:1. Seasonal variation followed a unimodal shape with a rate ratio of 1.13 from the average, peaking in March and reaching the lowest in September. After adjusting for seasonality and long-term trend, every one-degree Celsius increase in the monthly mean temperature significantly increased the risk of developing KD by 8.28% (95% CI: 2.12%, 14.80%). Season-specific analysis revealed a positive association during the dry season (RR: 1.06, 95% CI: 1.01, 1.11), whereas no evidence of association was found during the wet season (RR: 1.10, 95% CI: 0.95, 1.27). Conclusion: We have presented the incidence of KD in the Philippines which is relatively varied from its neighboring countries. The unimodal seasonality of KD and its linear association with temperature, independent of season and secular trend, especially during dry season, may provide insights into its etiology and may support enhanced KD detection efforts in the country.

Seasonality of mortality under climate change: a multicountry projection study.

BACKGROUND: Climate change can directly impact temperature-related excess deaths and might subsequently change the seasonal variation in mortality. In this study, we aimed to provide a systematic and comprehensive assessment of potential future changes in the seasonal variation, or seasonality, of mortality across different climate zones. METHODS: In this modelling study, we collected daily time series of mean temperature and mortality (all causes or non-external causes only) via the Multi-Country Multi-City Collaborative (MCC) Research Network. These data were collected during overlapping periods, spanning from Jan 1, 1969 to Dec 31, 2020. We projected daily mortality from Jan 1, 2000 to Dec 31, 2099, under four climate change scenarios corresponding to increasing emissions (Shared Socioeconomic Pathways [SSP] scenarios SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). We compared the seasonality in projected mortality between decades by its shape, timings (the day-of-year) of minimum (trough) and maximum (peak) mortality, and sizes (peak-to-trough ratio and attributable fraction). Attributable fraction was used to measure the burden of seasonality of mortality. The results were summarised by climate zones. FINDINGS: The MCC dataset included 126 809 537 deaths from 707 locations within 43 countries or areas. After excluding the only two polar locations (both high-altitude locations in Peru) from climatic zone assessments, we analysed 126 766 164 deaths in 705 locations aggregated in four climate zones (tropical, arid, temperate, and continental). From the 2000s to the 2090s, our projections showed an increase in mortality during the warm seasons and a decrease in mortality during the cold seasons, albeit with mortality remaining high during the cold seasons, under all four SSP scenarios in the arid, temperate, and continental zones. The magnitude of this changing pattern was more pronounced under the high-emission scenarios (SSP3-7.0 and SSP5-8.5), substantially altering the shape of seasonality of mortality and, under the highest emission scenario (SSP5-8.5), shifting the mortality peak from cold seasons to warm seasons in arid, temperate, and continental zones, and increasing the size of seasonality in all zones except the arid zone by the end of the century. In the 2090s compared with the 2000s, the change in peak-to-trough ratio (relative scale) ranged from 0·96 to 1·11, and the change in attributable fraction ranged from 0·002% to 0·06% under the SSP5-8.5 (highest emission) scenario. INTERPRETATION: A warming climate can substantially change the seasonality of mortality in the future. Our projections suggest that health-care systems should consider preparing for a potentially increased demand during warm seasons and sustained high demand during cold seasons, particularly in regions characterised by arid, temperate, and continental climates. FUNDING: The Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency, provided by the Ministry of the Environment of Japan.

Time-stratified case-crossover studies for aggregated data in environmental epidemiology: a tutorial.

The case-crossover design is widely used in environmental epidemiology as an effective alternative to the conventional time-series regression design to estimate short-term associations of environmental exposures with a range of acute events. This tutorial illustrates the implementation of the time-stratified case-crossover design to study aggregated health outcomes and environmental exposures, such as particulate matter air pollution, focusing on adjusting covariates and investigating effect modification using conditional Poisson regression. Time-varying confounders can be adjusted directly in the conditional regression model accounting for the adequate lagged exposure-response function. Time-invariant covariates at the subpopulation level require reshaping the typical time-series data set into a long format and conditioning out the covariate in the expanded stratum set. When environmental exposure data are available at geographical units, the stratum set should combine time and spatial dimensions. Moreover, it is possible to examine effect modification using interaction models. The time-stratified case-crossover design offers a flexible framework to properly account for a wide range of covariates in environmental epidemiology studies.

Reconstructing individual-level exposures in cohort analyses of environmental risks: an example with the UK Biobank.

Recent developments in linkage procedures and exposure modelling offer great prospects for cohort analyses on the health risks of environmental factors. However, assigning individual-level exposures to large population-based cohorts poses methodological and practical problems. In this contribution, we illustrate a linkage framework to reconstruct environmental exposures for individual-level epidemiological analyses, discussing methodological and practical issues such as residential mobility and privacy concerns. The framework outlined here requires the availability of individual residential histories with related time periods, as well as high-resolution spatio-temporal maps of environmental exposures. The linkage process is carried out in three steps: (1) spatial alignment of the exposure maps and residential locations to extract address-specific exposure series; (2) reconstruction of individual-level exposure histories accounting for residential changes during the follow-up; (3) flexible definition of exposure summaries consistent with alternative research questions and epidemiological designs. The procedure is exemplified by the linkage and processing of daily averages of air pollution for the UK Biobank cohort using gridded spatio-temporal maps across Great Britain. This results in the extraction of exposure summaries suitable for epidemiological analyses of both short and long-term risk associations and, in general, for the investigation of temporal dependencies. The linkage framework presented here is generally applicable to multiple environmental stressors and can be extended beyond the reconstruction of residential exposures. IMPACT: This contribution describes a linkage framework to assign individual-level environmental exposures to population-based cohorts using high-resolution spatio-temporal exposure. The framework can be used to address current limitations of exposure assessment for the analysis of health risks associated with environmental stressors. The linkage of detailed exposure information at the individual level offers the opportunity to define flexible exposure summaries tailored to specific study designs and research questions. The application of the framework is exemplified by the linkage of fine particulate matter (PM2.5) exposures to the UK Biobank cohort.

A Nationwide Comparative Analysis of Temperature-Related Mortality and Morbidity in Japan.

BACKGROUND: The impact of temperature on morbidity remains largely unknown. Moreover, extensive evidence indicates contrasting patterns between temperature-mortality and temperature-morbidity associations. A nationwide comparison of the impact of temperature on mortality and morbidity in more specific subgroups is necessary to strengthen understanding and help explore underlying mechanisms by identifying susceptible populations. OBJECTIVE: We performed this study to quantify and compare the impact of temperature on mortality and morbidity in 47 prefectures in Japan. METHODS: We applied a two-stage time-series design with distributed lag nonlinear models and mixed-effect multivariate meta-analysis to assess the association of temperature with mortality and morbidity by causes (all-cause, circulatory, and respiratory) at prefecture and country levels between 2015 and 2019. Subgroup analysis was conducted by sex, age, and regions. RESULTS: The patterns and magnitudes of temperature impacts on morbidity and mortality differed. For all-cause outcomes, cold exhibited larger effects on mortality, and heat showed larger effects on morbidity. At specific temperature percentiles, cold (first percentile) was associated with a higher relative risk (RR) of mortality [1.45; 95% confidence interval (CI): 1.39, 1.52] than morbidity (1.33; 95% CI: 1.26, 1.40), as compared to the minimum mortality/morbidity temperature. Heat (99th percentile) was associated with a higher risk of morbidity (1.30; 95% CI: 1.28, 1.33) than mortality (1.04; 95% CI: 1.02, 1.06). For cause-specific diseases, mortality due to circulatory diseases was more susceptible to heat and cold than morbidity. However, for respiratory diseases, both cold and heat showed higher risks for morbidity than mortality. Subgroup analyses suggested varied associations depending on specific outcomes. DISCUSSION: Distinct patterns were observed for the association of temperature with mortality and morbidity, underlying different mechanisms of temperature on different end points, and the differences in population susceptibility are possible explanations. Future mitigation policies and preventive measures against nonoptimal temperatures should be specific to disease outcomes and targeted at susceptible populations. https://doi.org/10.1289/EHP12854.

High Summer Temperatures and Heat Stroke Mortality in Spain.

BACKGROUND: Heat stroke is a significant cause of mortality in response to high summer temperatures. There is limited evidence on the pattern and magnitude of the association between temperature and heat stroke mortality. We examined this association in Spain, using data from a 27-year follow-up period. METHODS: We used a space-time-stratified case-crossover design. We analyzed data using conditional quasi-Poisson regression with distributed lag nonlinear models. RESULTS: Spain recorded a total of 285 heat stroke deaths between 1990 and 2016. Heat stroke deaths occurred in 6% of the days in the summer months. The mean temperature was, on average, 5 °C higher on days when a heat stroke was recorded than on days without heat stroke deaths. The overall relative risk was 1.74 (95% confidence interval = 1.54, 1.96) for a 1 °C rise in mean temperature above the threshold of 16 °C, at which a heat stroke death was first recorded. We observed lagged effects as long as 10 days. CONCLUSIONS: Although heat stroke represents a small fraction of total heat-attributable mortality during the summer, it is strongly associated with high temperatures, providing an immediately visible warning of heat-related risk.

Role of oxides of nitrogen in the ozone-cardiorespiratory visit association.

Ozone (O3)-induced health effects vary in terms of severity, from deterioration of lung function and hospitalization to death. Several studies have reported a linear increase in health risks after O3 exposure. However, current evidence suggests a non-linear U- and J-shaped concentration-response (C-R) function. The potential increasing risks with decreasing O3 concentrations may seem counterintuitive from the traditional standpoint that decreasing exposure should lead to decreasing health risks. Tus, the question of whether the increasing risks with decreasing concentrations are truly O3-induced or might be from other C-R mechanisms. If these potential risks were not accounted for, this may have contributed to the risks observed at the low ozone concentration range. In this study, we examined the short-term effects of photochemical oxidant (Ox, parts per billiion) on outpatient cardiorespiratory visits in 21 Japanese cities after adjusting for other air pollutant-specific C-R functions. Daily cardiorespiratory visits from January 1, 2014 to December 31, 2016 were obtained from the Japanese Medical Data Center Co. Ltd. Similar period of meteorological and air pollution variables were obtained from relevant data sources. We utilized a time-stratified case crossover design coupled with the generalized additive mixed model (TSCC-GAMM) to estimate the association between Ox and cardiorespiratory outpatient visits, after adjusting for several covariates. A total of 2,588,930 visits were recorded across the study period, with a mean of 111.87 and a standard deviation of 138.75. The results revealed that crude Ox-cardiorespiratory visits exhibited a U-shaped pattern. However, adjustment of the oxides of nitrogen, particularly nitrogen monoxide (NO), attenuated the lower risk curve and subsequently altered the shape of the C-R function, with a substantial reduction observed during winter. NO- and nitrogen dioxide (NO2)-adjusted Ox-cardiorespiratory associations increased nearly linearly, without an apparent threshold. Current evidence suggests the importance of adjusting the oxides of nitrogen in estimating the Ox C-R risk functions.

Long-term trends in mortality risk associated with short-term exposure to air pollution in 10 Japanese cities between 1977 and 2015.

BACKGROUND AND AIM: Short-term associations between air pollution and mortality have been well reported in Japan, but the historical changes in mortality risk remain unknown. We examined temporal changes in the mortality risks associated with short-term exposure to four criteria air pollutants in selected Japanese cities. METHODS: We collected daily mortality data for non-accidental causes (n = 5,748,206), cardiovascular (n = 1,938,743) and respiratory diseases (n = 777,266), and air pollutants (sulfur dioxide [SO2], nitrogen dioxide [NO2], suspended particulate matter [SPM], and oxidants [Ox]) in 10 cities from 1977 to 2015. We performed two-stage analysis with 5-year stratification to estimate the relative risk (RR) of mortality per 10-unit increase in the 2-day moving average of air pollutant concentrations. In the first stage, city-specific associations were assessed using a quasi-Poisson generalized linear regression model. In the second stage, city-specific estimates were pooled using a random-effects meta-analysis. Linear trend and ratio of relative risks (RRR) were computed to examine temporal changes. RESULTS: When stratifying the analysis by every 5 years, average concentrations in each sub-period decreased for SO2, NO2, and SPM (14.2-2.3 ppb, 29.4-17.5 ppb, 52.1-20.6 µg/m3, respectively) but increased for Ox (29.1-39.1 ppb) over the study period. We found evidence of a negative linear trend in the risk of cardiovascular mortality associated with SPM across sub-periods. However, the risks of non-accidental and respiratory mortality per 10-unit increase in SPM concentration were significantly higher in the most recent period than in the earliest period. Other gaseous pollutants did not show such temporal risk change. The risks posed by these pollutants were slightly to moderately heterogeneous in the different cities. CONCLUSIONS: The mortality risks associated with short-term exposure to SPM changed, with different trends by cause of death, in 10 cities over 39 years whereas the risks for other gaseous pollutants were relatively stable.

Effect of pneumococcal conjugate vaccine on prevalence of otitis media with effusion among children in Vietnam.

PURPOSE: Otitis media with effusion (OME) is common in young children and is associated with Streptococcus pneumoniae infection. We aimed to determine the impact of pneumococcal conjugate vaccine (PCV) introduction on the prevalence of OME and OME associated with vaccine-type (VT) or non-VT. METHODS: Population-based cross-sectional surveys were conducted in pre- (2016) and post-PCV periods (2017, 2018, and 2019) at selected communes in Nha Trang, Vietnam. For each survey, we randomly selected 60 children aged 4-11 months and 60 aged 14-23 months from each commune. Nasopharyngeal sample collection and tympanic membrane examination by digital otoscope were performed. S. pneumoniae was detected and serotyped by lytA qPCR and microarray. Odds ratios (OR) and 95% confidence intervals (CIs) were calculated using Firth's logistic regression, stratified by age group. RESULTS: Over the four surveys, 2089 children had a bilateral ear examination. Compared to pre-PCV, the prevalence of OME reduced in 2018 (OR 0.51, 95 %CI 0.28-0.93) and in 2019 (OR 0.53, 95 %CI 0.29-0.97) among the <12-month-olds, but no significant reduction among the 12-23-month-olds. The prevalence of OME associated with VT pneumococcus decreased in 2018 and 2019 (2018: OR 0.14, 95 %CI 0.03-0.55; 2019: OR 0.20, 95 %CI 0.05-0.69 in the <12-months-olds, 2018: OR 0.05, 95 %CI 0.00-0.44, 2019: OR 0.41, 95 %CI 0.10-1.61 in the 12-23-months-olds). The prevalence of OME associated with non-VT pneumococcus increased in the 12-23-month-olds in 2017 (OR 3.09, 95 %CI 1.47-7.45) and returned to the pre-PCV level of prevalence in 2018 and 2019 (OR 0.94, 95 %CI 0.40-2.43 and 1.40, 95 %CI 0.63-3.49). CONCLUSION: PCV10 introduction was associated with a reduction of OME prevalence in infants but not in older children.

Assessing seasonality and the role of its potential drivers in environmental epidemiology: a tutorial.

Several methods have been used to assess the seasonality of health outcomes in epidemiological studies. However, little information is available on the methods to study the changes in seasonality before and after adjusting for environmental or other known seasonally varying factors. Such investigations will help us understand the role of these factors in seasonal variation in health outcomes and further identify currently unknown or unmeasured risk factors. This tutorial illustrates a statistical procedure for examining the seasonality of health outcomes and their changes, after adjusting for potential environmental drivers by assessing and comparing shape, timings and size. We recommend a three-step procedure, each carried out and compared before and after adjustment: (i) inspecting the fitted seasonal curve to determine the broad shape of seasonality; (ii) identifying the peak and trough of seasonality to determine the timings of seasonality; and (iii) estimating the peak-to-trough ratio and attributable fraction to measure the size of seasonality. Reporting changes in these features on adjusting for potential drivers allows readers to understand their role in seasonality and the nature of any residual seasonal pattern. Furthermore, the proposed approach can be extended to other health outcomes and environmental drivers.

Projecting Temperature-Attributable Mortality and Hospital Admissions due to Enteric Infections in the Philippines.

BACKGROUND: Enteric infections cause significant deaths, and global projection studies suggest that mortality from enteric infections will increase in the future with warmer climate. However, a major limitation of these projection studies is the use of risk estimates derived from nonmortality data to project excess enteric infection mortality associated with temperature because of the lack of studies that used actual deaths. OBJECTIVE: We quantified the associations of daily temperature with both mortality and hospital admissions due to enteric infections in the Philippines. These associations were applied to projections under various climate and population change scenarios. METHODS: We modeled nonlinear temperature associations of mortality and hospital admissions due to enteric infections in 17 administrative regions of the Philippines using a two-stage time-series approach. First, we quantified nonlinear temperature associations of enteric infections by fitting generalized linear models with distributed lag nonlinear models. Second, we combined regional estimates using a meta-regression model. We projected the excess future enteric infections due to nonoptimal temperatures using regional temperature-enteric infection associations under various combinations of climate change scenarios according to representative concentration pathways (RCPs) and population change scenarios according to shared socioeconomic pathways (SSPs) for 2010-2099. RESULTS: Regional estimates for mortality and hospital admissions were significantly heterogeneous and had varying shapes in association with temperature. Generally, mortality risks were greater in high temperatures, whereas hospital admission risks were greater in low temperatures. Temperature-attributable excess deaths in 2090-2099 were projected to increase over 2010-2019 by as little as 1.3% [95% empirical confidence intervals (eCI): -3.1%, 6.5%] under a low greenhouse gas emission scenario (RCP 2.6) or as much as 25.5% (95% eCI: -3.5%, 48.2%) under a high greenhouse gas emission scenario (RCP 8.5). A moderate increase was projected for temperature-attributable excess hospital admissions, from 0.02% (95% eCI: -2.0%, 1.9%) under RCP 2.6 to 5.2% (95% eCI: -12.7%, 21.8%) under RCP 8.5 in the same period. High temperature-attributable deaths and hospital admissions due to enteric infections may occur under scenarios with high population growth in 2090-2099. DISCUSSION: In the Philippines, futures with hotter temperatures and high population growth may lead to a greater increase in temperature-related excess deaths than hospital admissions due to enteric infections. Our results highlight the need to strengthen existing primary health care interventions for diarrhea and support health adaptation policies to help reduce future enteric infections. https://doi.org/10.1289/EHP9324.

The seroprevalence, waning rate, and protective duration of anti-diphtheria toxoid IgG antibody in Nha Trang, Vietnam.

BACKGROUND: Diphtheria cases reported in Central Vietnam since 2013 were mainly in children aged 6-15 years, which may reflect an immunity gap. There is little information on population immunity against diphtheria in countries without a school-entry booster dose. We aimed to measure the age-stratified seroprevalence of anti-diphtheria toxoid antibodies, quantify the change in antibody levels in individuals over time, and estimate the length of protective immunity after vaccination in well-vaccinated communities in Vietnam. METHODS: An age-stratified seroprevalence survey among individuals aged 0-55 years was conducted at Nha Trang, Vietnam. The same participants were followed up after two years to quantify the change in antibody levels. IgG was measured using ELISA. The length of protective immunity after vaccination was estimated using a mixed-effect linear regression model with random intercept. RESULTS: Overall seroprevalence was 26% (95%CI:20-32%). Age-stratified seroprevalence was 68% (95%CI:4-11%), 7% (95%CI:4-11%), 12% (95%CI:7-19%), 33% (95%CI:27-40%), and 28% (95%CI:17-43%) among those aged ≤5, 6-15,16-25, 26-35, and 36-55 years, respectively. The antibody levels declined by 47% (95%CI:31-59%) over two years, and the predicted duration of vaccine-derived protective immunity after receiving four doses was 4.3 years (95%CI:3.5-5.3) among participants aged six years or younger. CONCLUSION: Given the low seroprevalence and short period of vaccine protection, a school-entry booster dose (5-7 years) is recommended in Vietnam.

Early life exposure to indoor air pollutants and the risk of neurodevelopmental delays: The Japan Environment and Children's Study.

Air pollution has been associated with childhood neurodevelopment. However, the role of indoor air pollution, especially volatile organic compounds (VOCs), on childhood neurodevelopment has been poorly explored to date. We investigated the association between indoor air pollutants and childhood neurodevelopment in 5,017 randomly selected children from the Japan Environment and Children's Study. When the participants reached 1.5 and 3 years of age, they were followed up with home visits and neurodevelopmental tests using the Ages and Stages Questionnaire (ASQ). At both ages, we collected indoor air samples for 1 week and measured 13 indoor air pollutants: particulate matter with an aerodynamic diameter of ≤2.5 µm, ozone, nitrogen dioxide, sulfur dioxide, and nine VOCs. The associations between air pollutants and ASQ scores were estimated using linear mixed effects models and weighted quantile sum regressions (WQS) at each age separately. Stratified analysis by sex was conducted. Exposure to m,p-xylene at the age of 3 was associated with lower communication, fine motor, and overall ASQ scores (coefficients: -0.18 [99% confidence intervals (CI): -0.35, -0.02], -0.23 [99 %CI: -0.43, -0.03], and - 0.72 [99 %CI: -1.41, -0.04] per 1 µg/m3 increase, respectively). Exposure to o-xylene at the age of 3 was associated with lower communication, gross motor, fine motor, and overall ASQ scores (coefficients: -0.48 [99 %CI: -0.90, -0.07], -0.45 [99 %CI: -0.78, -0.13], -0.65 [99 %CI: -1.14, -0.16], and -2.15 [99 %CI: -3.83, -0.47] per 1 µg/m3 increase, respectively). The WQS index was associated with lower gross motor ASQ scores at the age of 3 (coefficient: -0.27 [95 %CI: -0.51, -0.03] for one-unit WQS index increases), which was attributed to benzene (33.96%), toluene (26.02%), o-xylene (13.62%), and ethylbenzene (9.83%). Stratified analysis showed similar results. Although further investigations are required, our results suggest an association of neurodevelopmental delays with indoor low-level exposure to m,p-xylene and o-xylene in early life.

Seasonal variation in mortality and the role of temperature: a multi-country multi-city study.

BACKGROUND: Although seasonal variations in mortality have been recognized for millennia, the role of temperature remains unclear. We aimed to assess seasonal variation in mortality and to examine the contribution of temperature. METHODS: We compiled daily data on all-cause, cardiovascular and respiratory mortality, temperature and indicators on location-specific characteristics from 719 locations in tropical, dry, temperate and continental climate zones. We fitted time-series regression models to estimate the amplitude of seasonal variation in mortality on a daily basis, defined as the peak-to-trough ratio (PTR) of maximum mortality estimates to minimum mortality estimates at day of year. Meta-analysis was used to summarize location-specific estimates for each climate zone. We estimated the PTR with and without temperature adjustment, with the differences representing the seasonal effect attributable to temperature. We also evaluated the effect of location-specific characteristics on the PTR across locations by using meta-regression models. RESULTS: Seasonality estimates and responses to temperature adjustment varied across locations. The unadjusted PTR for all-cause mortality was 1.05 [95% confidence interval (CI): 1.00-1.11] in the tropical zone and 1.23 (95% CI: 1.20-1.25) in the temperate zone; adjusting for temperature reduced the estimates to 1.02 (95% CI: 0.95-1.09) and 1.10 (95% CI: 1.07-1.12), respectively. Furthermore, the unadjusted PTR was positively associated with average mean temperature. CONCLUSIONS: This study suggests that seasonality of mortality is importantly driven by temperature, most evidently in temperate/continental climate zones, and that warmer locations show stronger seasonal variations in mortality, which is related to a stronger effect of temperature.

Respiratory Syncytial Virus Outbreaks Are Predicted after the COVID-19 Pandemic in Tokyo, Japan.

Nonpharmaceutical interventions (NPIs) for COVID-19 can affect the current and future dynamics of respiratory syncytial virus infections (RSV). In Tokyo, RSV activity declined by 97.9% (95% CI: 94.8%-99.2%) during NPIs. A long period of NPIs could increase susceptible populations, thus enhancing the potential for large RSV outbreaks after the end of NPIs.

COVID-19 pandemic modifies temperature and heat-related illness ambulance transport association in Japan: a nationwide observational study.

BACKGROUND: During the COVID-19 pandemic, several illnesses were reduced. In Japan, heat-related illnesses were reduced by 22% compared to pre-pandemic period. However, it is uncertain as to what has led to this reduction. Here, we model the association of maximum temperature and heat-related illnesses in the 47 Japanese prefectures. We specifically examined how the exposure and lag associations varied before and during the pandemic. METHODS: We obtained the summer-specific, daily heat-related illness ambulance transport (HIAT), exposure variable (maximum temperature) and covariate data from relevant data sources. We utilized a stratified (pre-pandemic and pandemic), two-stage approach. In each stratified group, we estimated the 1) prefecture-level association using a quasi-Poisson regression coupled with a distributed lag non-linear model, which was 2) pooled using a random-effects meta-analysis. The difference between pooled pre-pandemic and pandemic associations was examined across the exposure and the lag dimensions. RESULTS: A total of 321,655 HIAT cases was recorded in Japan from 2016 to 2020. We found an overall reduction of heat-related risks for HIAT during the pandemic, with a wide range of reduction (10.85 to 57.47%) in the HIAT risk, across exposure levels ranging from 21.69 °C to 36.31 °C. On the contrary, we found an increment in the delayed heat-related risks during the pandemic at Lag 2 (16.33%; 95% CI: 1.00, 33.98%). CONCLUSION: This study provides evidence of the impact of COVID-19, particularly on the possible roles of physical interventions and behavioral changes, in modifying the temperature-health association. These findings would have implications on subsequent policies or heat-related warning strategies in light of ongoing or future pandemics.

Role of temperature, influenza and other local characteristics in seasonality of mortality: a population-based time-series study in Japan.

OBJECTIVES: To investigate the extent to which temperature and influenza explained seasonality of mortality in Japan and to examine the association of the seasonality with prefecture-specific characteristics. DESIGN: We conducted time-series analysis to estimate the seasonal amplitude before and after adjusting for temperature and/or influenza-like illness (ILI). Next, we applied linear mixed effect models to investigate the association of seasonal amplitudes with each indicator on prefecture-specific characteristics on climate, demographic and socioeconomic factors and adaptations. SETTING: 47 prefectures in Japan PARTICIPANTS: Deaths for all-cause, circulatory, and respiratory disease between 1999 and 2015. OUTCOME MEASURES: Peak-to-trough ratio (PTR, a measure of seasonal amplitude). RESULTS: The nationwide unadjusted-PTRs for all-cause, circulatory and respiratory mortality were 1.29 (95% CIs: 1.28 to 1.31), 1.55 (95% CI: 1.52 to 1.57) and 1.45 (95% CI: 1.43 to 1.48), respectively. These PTRs reduced substantially after adjusting for temperature but very little after a separate adjustment for ILI. Furthermore, seasonal amplitudes varied between prefectures. However, there was no strong evidence for the associations of PTR with the indicators on prefecture-specific characteristics. CONCLUSIONS: Seasonality of mortality is primarily driven by temperature in Japan. The spatial variation in seasonal amplitudes was not associated with prefecture-specific characteristics. Although further investigations are required to confirm our findings, this study can help us gain a better understanding of the mechanisms underlying seasonality of mortality.

Global projections of temperature-attributable mortality due to enteric infections: a modelling study.

BACKGROUND: Mortality due to enteric infections is projected to increase because of global warming; however, the different temperature sensitivities of major enteric pathogens have not yet been considered in projections on a global scale. We aimed to project global temperature-attributable enteric infection mortality under various future scenarios of sociodemographic development and climate change. METHODS: In this modelling study, we generated global projections in two stages. First, we forecasted baseline mortality from ten enteropathogens (non-typhoidal salmonella, Shigella, Campylobacter, cholera, enteropathogenic Escherichia coli, enterotoxigenic E coli, typhoid, rotavirus, norovirus, and Cryptosporidium) under several future sociodemographic development and health investment scenarios (ie, pessimistic, intermediate, and optimistic). We then estimated the mortality change from baseline attributable to global warming using the product of projected annual temperature anomalies and pathogen-specific temperature sensitivities. FINDINGS: We estimated that in the period 2080-95, the global mean number of temperature-attributable deaths due to enteric infections could be as low as 6599 (95% empirical CI 5441-7757) under the optimistic sociodemographic development and climate change scenario, or as high as 83 888 (67 760-100 015) under the pessimistic scenario. Most of the projected temperature-attributable deaths were from shigellosis, cryptosporidiosis, and typhoid fever in sub-Saharan Africa and South Asia. Considerable reductions in the number of attributable deaths were from viral infections, such as rotaviral and noroviral enteritis, which resulted in net reductions in attributable enteric infection mortality under optimistic scenarios for Latin America and the Caribbean and East Asia and the Pacific. INTERPRETATION: Temperature-attributable mortality could increase under warmer climate and unfavourable sociodemographic conditions. Mitigation policies for limiting global warming and sociodemographic development policies for low-income and middle-income countries might help reduce mortality from enteric infections in the future. FUNDING: Japan Society for the Promotion of Science, Japan Science and Technology Agency, and Spanish Ministry of Economy, Industry, and Competitiveness.

Seasonality of mortality under a changing climate: a time-series analysis of mortality in Japan between 1972 and 2015.

BACKGROUND: Ambient temperature may contribute to seasonality of mortality; in particular, a warming climate is likely to influence the seasonality of mortality. However, few studies have investigated seasonality of mortality under a warming climate. METHODS: Daily mean temperature, daily counts for all-cause, circulatory, and respiratory mortality, and annual data on prefecture-specific characteristics were collected for 47 prefectures in Japan between 1972 and 2015. A quasi-Poisson regression model was used to assess the seasonal variation of mortality with a focus on its amplitude, which was quantified as the ratio of mortality estimates between the peak and trough days (peak-to-trough ratio (PTR)). We quantified the contribution of temperature to seasonality by comparing PTR before and after temperature adjustment. Associations between annual mean temperature and annual estimates of the temperature-unadjusted PTR were examined using multilevel multivariate meta-regression models controlling for prefecture-specific characteristics. RESULTS: The temperature-unadjusted PTRs for all-cause, circulatory, and respiratory mortality were 1.28 (95% confidence interval (CI): 1.27-1.30), 1.53 (95% CI: 1.50-1.55), and 1.46 (95% CI: 1.44-1.48), respectively; adjusting for temperature reduced these PTRs to 1.08 (95% CI: 1.08-1.10), 1.10 (95% CI: 1.08-1.11), and 1.35 (95% CI: 1.32-1.39), respectively. During the period of rising temperature (1.3 °C on average), decreases in the temperature-unadjusted PTRs were observed for all mortality causes except circulatory mortality. For each 1 °C increase in annual mean temperature, the temperature-unadjusted PTR for all-cause, circulatory, and respiratory mortality decreased by 0.98% (95% CI: 0.54-1.42), 1.39% (95% CI: 0.82-1.97), and 0.13% (95% CI: - 1.24 to 1.48), respectively. CONCLUSION: Seasonality of mortality is driven partly by temperature, and its amplitude may be decreasing under a warming climate.