Integrated causal-predictive machine learning models for tropical cyclone epidemiology

Tropical cyclone-specific mortality risks and the periods of concern: A multicountry time-series study

BACKGROUND

More intense tropical cyclones (TCs) are expected in the future under a warming climate scenario, but little is known about their mortality effect pattern across countries and over decades. We aim to evaluate the TC-specific mortality risks, periods of concern (POC) and characterize the spatiotemporal pattern and exposure-response (ER) relationships on a multicountry scale.

METHODS AND FINDINGS

Daily all-cause, cardiovascular, and respiratory mortality among the general population were collected from 494 locations in 18 countries or territories during 1980 to 2019. Daily TC exposures were defined when the maximum sustained windspeed associated with a TC was ≥34 knots using a parametric wind field model at a 0.5° × 0.5° resolution. We first estimated the TC-specific mortality risks and POC using an advanced flexible statistical framework of mixed Poisson model, accounting for the population changes, natural variation, seasonal and day of the week effects. Then, a mixed meta-regression model was used to pool the TC-specific mortality risks to estimate the overall and country-specific ER relationships of TC characteristics (windspeed, rainfall, and year) with mortality. Overall, 47.7 million all-cause, 15.5 million cardiovascular, and 4.9 million respiratory deaths and 382 TCs were included in our analyses. An overall average POC of around 20 days was observed for TC-related all-cause and cardiopulmonary mortality, with relatively longer POC for the United States of America, Brazil, and Taiwan (>30 days). The TC-specific relative risks (RR) varied substantially, ranging from 1.04 to 1.42, 1.07 to 1.77, and 1.12 to 1.92 among the top 100 TCs with highest RRs for all-cause, cardiovascular, and respiratory mortality, respectively. At country level, relatively higher TC-related mortality risks were observed in Guatemala, Brazil, and New Zealand for all-cause, cardiovascular, and respiratory mortality, respectively. We found an overall monotonically increasing and approximately linear ER curve of TC-related maximum sustained windspeed and cumulative rainfall with mortality, with heterogeneous patterns across countries and regions. The TC-related mortality risks were generally decreasing from 1980 to 2019, especially for the Philippines, Taiwan, and the USA, whereas potentially increasing trends in TC-related all-cause and cardiovascular mortality risks were observed for Japan.

CONCLUSIONS

The TC mortality risks and POC varied greatly across TC events, locations, and countries. To minimize the TC-related health burdens, targeted strategies are particularly needed for different countries and regions, integrating epidemiological evidence on region-specific POC and ER curves that consider across-TC variability.

A Bayesian multivariate factor analysis model for causal inference using time-series observational data on mixed outcomes

Assessing the impact of an intervention by using time-series observational data on multiple units and outcomes is a frequent problem in many fields of scientific research. Here, we propose a novel Bayesian multivariate factor analysis model for estimating intervention effects in such settings and develop an efficient Markov chain Monte Carlo algorithm to sample from the high-dimensional and nontractable posterior of interest. The proposed method is one of the few that can simultaneously deal with outcomes of mixed type (continuous, binomial, count), increase efficiency in the estimates of the causal effects by jointly modeling multiple outcomes affected by the intervention, and easily provide uncertainty quantification for all causal estimands of interest. Using the proposed approach, we evaluate the impact that Local Tracing Partnerships had on the effectiveness of England's Test and Trace programme for COVID-19.

Health Effects of Cyclones: A Systematic Review and Meta-Analysis of Epidemiological Studies

BACKGROUND

More intense cyclones are expected in the future as a result of climate change. A comprehensive review is urgently needed to summarize and update the evidence on the health effects of cyclones.

OBJECTIVES

We aimed to provide a systematic review with meta-analysis of current evidence on the risks of all reported health outcomes related to cyclones and to identify research gaps and make recommendations for further research.

METHODS

We systematically searched five electronic databases (MEDLINE, Embase, PubMed, Scopus, and Web of Science) for relevant studies in English published before 21 December 2022. Following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guidelines, we developed inclusion criteria, screened the literature, and included epidemiological studies with a quantitative risk assessment of any mortality or morbidity-related outcomes associated with cyclone exposures. We extracted key data and assessed study quality for these studies and applied meta-analyses to quantify the overall effect estimate and the heterogeneity of comparable studies.

RESULTS

In total, 71 studies from eight countries (the United States, China, India, Japan, the Philippines, South Korea, Australia, Brazil), mostly the United States, were included in the review. These studies investigated the all-cause and cause-specific mortality, as well as morbidity related to injury, cardiovascular diseases (CVDs), respiratory diseases, infectious diseases, mental disorders, adverse birth outcomes, cancer, diabetes, and other outcomes (e.g., suicide rates, gender-based violence). Studies mostly included only one high-amplitude cyclone (cyclones with a Saffir-Simpson category of 4 or 5, i.e., Hurricanes Katrina or Sandy) and focused on mental disorders morbidity and all-cause mortality and hospitalizations. Consistently elevated risks of overall mental health morbidity, post-traumatic stress disorder (PTSD), as well as all-cause mortality or hospitalizations, were found to be associated with cyclones. However, the results for other outcomes were generally mixed or limited. A statistically significant overall relative risk of 1.09 [95% confidence interval (CI): 1.04, 1.13], 1.18 (95% CI: 1.12, 1.25), 1.15 (95% CI: 1.13, 1.18), 1.26 (95% CI: 1.05, 1.50) was observed for all-cause mortality, all-cause hospitalizations, respiratory disease, and chronic obstructive pulmonary disease hospitalizations, respectively, after cyclone exposures, whereas no statistically significant risks were identified for diabetes mortality, heart disease mortality, and preterm birth. High between-study heterogeneity was observed.

CONCLUSIONS

There is generally consistent evidence supporting the notion that high-amplitude cyclones could significantly increase risks of mental disorders, especially for PTSD, as well as mortality and hospitalizations, but the evidence for other health outcomes, such as chronic diseases (e.g., CVDs, cancer, diabetes), and adverse birth outcomes remains limited or inconsistent. More studies with rigorous exposure assessment, of larger spatial and temporal scales, and using advanced modeling strategy are warranted in the future, especially for those small cyclone-prone countries or regions with low and middle incomes. https://doi.org/10.1289/EHP12158.

Impact of Hurricanes and Associated Extreme Weather Events on Cardiovascular Health: A Scoping Review

BACKGROUND

The frequency and destructiveness of hurricanes and related extreme weather events (e.g., cyclones, severe storms) have been increasing due to climate change. A growing body of evidence suggests that victims of hurricanes have increased incidence of cardiovascular disease (CVD), likely due to increased stressors around time of the hurricane and in their aftermath.

OBJECTIVES

The objective was to systematically examine the evidence of the association between hurricanes (and related extreme weather events) and adverse CVD outcomes with the goal of understanding the gaps in the literature.

METHODS

A comprehensive literature search of population-level and cohort studies focused on CVD outcomes (i.e., myocardial infarction, stroke, and heart failure) related to hurricanes, cyclones, and severe storms was performed in the following databases from inception to December 2021: Ovid MEDLINE, Ovid EMBASE, Web of Science, and The Cochrane Library. Studies retrieved were then screened for eligibility against predefined inclusion/exclusion criteria. Studies were then qualitatively synthesized based on the time frame of the CVD outcomes studied and special populations that were studied. Gaps in the literature were identified based on this synthesis.

RESULTS

Of the 1,103 citations identified, 48 met our overall inclusion criteria. We identified articles describing the relationship between CVD and extreme weather, primarily hurricanes, based on data from the United States (42), Taiwan (3), Japan (2), and France (1). Outcomes included CVD and myocardial infarction-related hospitalizations (30 studies) and CVVD-related mortality (7 studies). Most studies used a retrospective study design, including one case-control study, 39 cohort studies, and 4 time-series studies.

DISCUSSION

Although we identified a number of papers that reported evaluations of extreme weather events and short-term adverse CVD outcomes, there were important gaps in the literature. These gaps included a) a lack of rigorous long-term evaluation of hurricane exposure, b) lack of investigation of hurricane exposure on vulnerable populations regarding issues related to environmental justice, c) absence of research on the exposure of multiple hurricanes on populations, and d) absence of an exploration of mechanisms leading to worsened CVD outcomes. Future research should attempt to fill these gaps, thus providing an important evidence base for future disaster-related policy. https://doi.org/10.1289/EHP11252.

Exposure Assessment for Tropical Cyclone Epidemiology

PURPOSE OF REVIEW

Tropical cyclones impact human health, sometimes catastrophically. Epidemiological research characterizes these health impacts and uncovers pathways between storm hazards and health, helping to mitigate the health impacts of future storms. These studies, however, require researchers to identify people and areas exposed to tropical cyclones, which is often challenging. Here we review approaches, tools, and data products that can be useful in this exposure assessment.

RECENT FINDINGS

Epidemiological studies have used various operational measures to characterize exposure to tropical cyclones, including measures of physical hazards (e.g., wind, rain, flooding), measures related to human impacts (e.g., damage, stressors from the storm), and proxy measures of distance from the storm's central track. The choice of metric depends on the research question asked by the study, but there are numerous resources available that can help in capturing any of these metrics of exposure. Each has strengths and weaknesses that may influence their utility for a specific study. Here we have highlighted key tools and data products that can be useful for exposure assessment for tropical cyclone epidemiology. These results can guide epidemiologists as they design studies to explore how tropical cyclones influence human health.