Medicolegal Death Scene Investigations After Natural Disaster- and Weather-Related Events: A Review of the Literature

Mortality risks associated with floods in 761 communities worldwide: time series study

OBJECTIVE

To evaluate lag-response associations and effect modifications of exposure to floods with risks of all cause, cardiovascular, and respiratory mortality on a global scale.

DESIGN

Time series study.

SETTING

761 communities in 35 countries or territories with at least one flood event during the study period.

PARTICIPANTS

Multi-Country Multi-City Collaborative Research Network database, Australian Cause of Death Unit Record File, New Zealand Integrated Data Infrastructure, and the International Network for the Demographic Evaluation of Populations and their Health Network database.

MAIN OUTCOME MEASURES

The main outcome was daily counts of deaths. An estimation for the lag-response association between flood and daily mortality risk was modelled, and the relative risks over the lag period were cumulated to calculate overall effects. Attributable fractions of mortality due to floods were further calculated. A quasi-Poisson model with a distributed lag non-linear function was used to examine how daily death risk was associated with flooded days in each community, and then the community specific associations were pooled using random effects multivariate meta-analyses. Flooded days were defined as days from the start date to the end date of flood events.

RESULTS

A total of 47.6 million all cause deaths, 11.1 million cardiovascular deaths, and 4.9 million respiratory deaths were analysed. Over the 761 communities, mortality risks increased and persisted for up to 60 days (50 days for cardiovascular mortality) after a flooded day. The cumulative relative risks for all cause, cardiovascular, and respiratory mortality were 1.021 (95% confidence interval 1.006 to 1.036), 1.026 (1.005 to 1.047), and 1.049 (1.008 to 1.092), respectively. The associations varied across countries or territories and regions. The flood-mortality associations appeared to be modified by climate type and were stronger in low income countries and in populations with a low human development index or high proportion of older people. In communities impacted by flood, up to 0.10% of all cause deaths, 0.18% of cardiovascular deaths, and 0.41% of respiratory deaths were attributed to floods.

CONCLUSIONS

This study found that the risks of all cause, cardiovascular, and respiratory mortality increased for up to 60 days after exposure to flood and the associations could vary by local climate type, socioeconomic status, and older age.

Community-wide Mortality Rates in Beijing, China, During the July 2012 Flood Compared with Unexposed Periods

BACKGROUND

On 21-22 July 2012, Beijing, China, suffered its heaviest rainfall in 60 years. Two studies have estimated the fatality toll of this disaster using a traditional surveillance approach. However, traditional surveillance can miss disaster-related deaths, including a substantial number of deaths from natural causes triggered by disaster exposure. Here, we investigated community-wide mortality risk during this flood compared with rates in unexposed reference periods.

METHODS

We compared community-wide mortality rates on the peak flood day and the four following days to seasonally matched nonflood days in previous years (2008-2011), controlling for potential confounders, to estimate the relative risks (RRs) of daily mortality among Beijing residents associated with this flood.

RESULTS

On 21 July 2012, the flood-associated RRs were 1.34 (95% confidence interval = 1.11, 1.61) for all-cause, 1.37 (1.01, 1.85) for circulatory, and 4.40 (2.98, 6.51) for accidental mortality, compared with unexposed periods. We observed no evidence of increased risk of respiratory mortality. For the flood period of 21-22 July 2012, we estimated a total of 79 excess deaths among Beijing residents; by contrast, only 34 deaths were reported among Beijing residents in a study using a traditional surveillance approach.

CONCLUSIONS

To our knowledge, this is the first study analyzing community-wide changes in mortality rates during the 2012 flood in Beijing and one of the first to do so for any major flood worldwide. This study offers critical evidence on flood-related health impacts, as urban flooding is expected to become more frequent and severe in China.

Assessing United States County-Level Exposure for Research on Tropical Cyclones and Human Health

BACKGROUND

Tropical cyclone epidemiology can be advanced through exposure assessment methods that are comprehensive and consistent across space and time, as these facilitate multiyear, multistorm studies. Further, an understanding of patterns in and between exposure metrics that are based on specific hazards of the storm can help in designing tropical cyclone epidemiological research.

OBJECTIVES

a) Provide an open-source data set for tropical cyclone exposure assessment for epidemiological research; and b) investigate patterns and agreement between county-level assessments of tropical cyclone exposure based on different storm hazards.

METHODS

We created an open-source data set with data at the county level on exposure to four tropical cyclone hazards: peak sustained wind, rainfall, flooding, and tornadoes. The data cover all eastern U.S. counties for all land-falling or near-land Atlantic basin storms, covering 1996-2011 for all metrics and up to 1988-2018 for specific metrics. We validated measurements against other data sources and investigated patterns and agreement among binary exposure classifications based on these metrics, as well as compared them to use of distance from the storm's track, which has been used as a proxy for exposure in some epidemiological studies.

RESULTS

Our open-source data set was typically consistent with data from other sources, and we present and discuss areas of disagreement and other caveats. Over the study period and area, tropical cyclones typically brought different hazards to different counties. Therefore, when comparing exposure assessment between different hazard-specific metrics, agreement was usually low, as it also was when comparing exposure assessment based on a distance-based proxy measurement and any of the hazard-specific metrics.

DISCUSSION

Our results provide a multihazard data set that can be leveraged for epidemiological research on tropical cyclones, as well as insights that can inform the design and analysis for tropical cyclone epidemiological research. https://doi.org/10.1289/EHP6976.

Evaluation of Oklahoma's Electronic Death Registration System and Event Fatality Markers for Disaster-Related Mortality Surveillance - Oklahoma USA, May 2013

INTRODUCTION

Official counts of deaths attributed to disasters are often under-reported, thus adversely affecting public health messaging designed to prevent further mortality. During the Oklahoma (USA) May 2013 tornadoes, Oklahoma State Health Department Division of Vital Records (VR; Oklahoma City, Oklahoma USA) piloted a flagging procedure to track tornado-attributed deaths within its Electronic Death Registration System (EDRS). To determine if the EDRS was capturing all tornado-attributed deaths, the Centers for Disease Control and Prevention (CDC; Atlanta, Georgia USA) evaluated three event fatality markers (EFM), which are used to collate information about deaths for immediate response and retrospective research efforts.

METHODS

Oklahoma identified 48 tornado-attributed deaths through a retrospective review of hospital morbidity and mortality records. The Centers for Disease Control and Prevention (CDC; Atlanta, Georgia USA) analyzed the sensitivity, timeliness, and validity for three EFMs, which included: (1) a tornado-specific flag on the death record; (2) a tornado-related term in the death certificate; and (3) X37, the International Classification of Diseases, 10th Revision (ICD-10) code in the death record for Victim of a Cataclysmic Storm, which includes tornadoes.

RESULTS

The flag was the most sensitive EFM (89.6%; 43/48), followed by the tornado term (75.0%; 36/48), and the X37 code (56.2%; 27/48). The most-timely EFM was the flag, which took 2.0 median days to report (range 0-10 days), followed by the tornado term (median 3.5 days; range 1-21), and the X37 code (median >10 days; range 2-122). Over one-half (52.1%; 25/48) of the tornado-attributed deaths were missing at least one EFM. Twenty-six percent (11/43) of flagged records had no tornado term, and 44.1% (19/43) had no X37 code. Eleven percent (4/36) of records with a tornado term did not have a flag.

CONCLUSION

The tornado-specific flag was the most sensitive and timely EFM. Using the flag to collate death records and identify additional deaths without the tornado term and X37 code may improve immediate response and retrospective investigations. Moreover, each of the EFMs can serve as quality controls for the others to maximize capture of all disaster-attributed deaths from vital statistics records in the EDRS.Issa AN, Baker K, Pate D, Law R, Bayleyegn T, Noe RS. Evaluation of Oklahoma's Electronic Death Registration System and event fatality markers for disaster-related mortality surveillance - Oklahoma USA, May 2013. Prehosp Disaster Med. 2019;34(2):125-131.