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Statistical Methods for Mortality and Mobility Estimation after Natural Disasters.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Statistical Methods for Mortality and Mobility Estimation after Natural Disasters./
作者:	Acosta Nunez, Rolando J.
面頁冊數:	1 online resource (129 pages)
附註:	Source: Dissertations Abstracts International, Volume: 83-12, Section: B.
Contained By:	Dissertations Abstracts International83-12B.
標題:	Biostatistics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29209271click for full text (PQDT)
ISBN:	9798819381816

Statistical Methods for Mortality and Mobility Estimation after Natural Disasters.
Acosta Nunez, Rolando J.

Statistical Methods for Mortality and Mobility Estimation after Natural Disasters. - 1 online resource (129 pages)

Source: Dissertations Abstracts International, Volume: 83-12, Section: B.

Thesis (Ph.D.)--Harvard University, 2022.

Includes bibliographical references

Population displacement may occur after natural disasters, permanently altering the demographic compositionof the affected regions. Measuring this displacement is vital for both optimal post-disaster resourceallocation and calculation of measures of public health interest. Furthermore, quantifying the impact ofnatural disasters or epidemics is critical for guiding policy decisions and interventions. When the effectsof an event are long-lasting and difficult to detect in the short term, the accumulated effects can be devastating.Mortality is one of the most reliably measured health outcomes, partly due to its unambiguousdefinition. As a result, excess mortality estimates are an increasingly effective approach for quantifyingthe effect of an event. In Chapter 1 we analyzed data generated by mobile phones and social media to estimatethe weekly island-wide population at risk and within-island geographic heterogeneity of migrationin Puerto Rico after Hurricane Maria. We compared these two data sources with population estimatesderived from air travel records and census data. We observed a loss of population across all data sourcesthroughout the study period; however, the magnitude and dynamics differ by the data source. On average,municipalities with a smaller population size lost a bigger proportion of their population. Finally, ouranalysis measures a general shift of population from rural to urban centers within the island. In Chapter2 we present a model that accounts for sources of variation associated with mortality and characterizesconcerning increases in mortality rates with smooth functions of time that provide statistical power. Themodel allows for discontinuities in the smooth functions to model sudden increases due to direct effects.Finally, we implement a flexible estimation approach that permits both surveillance of such increases inmortality rates and careful characterization of the effect of a past event. We demonstrate our method's utilityby estimating excess mortality after hurricanes and epidemics in the United States and Puerto Rico, anduse Hurricane Maria as a case study to show appealing properties that are unique to our method comparedto current approaches. In Chapter 3 we use data from civil death registers from a convenience sample of90 municipalities across the state of Gujarat, India, to estimate the impact of the COVID-19 pandemic onall-cause mortality. Using a model fit to weekly data from January 2019 to February 2020, we estimated excessmortality over the course of the pandemic from March 2020 to April 2021. We estimated 21,300 [95%CI: 20,700, 22,000] excess deaths across these municipalities in this period, representing a 44% [95% CI:43%, 45%] increase over the expected baseline. The sharpest increase in deaths in our sample was observedin late April 2021, with an estimated 678% [95% CI: 649%, 707%] increase in mortality from expectedcounts. Our excess mortality estimate for these 90 municipalities, representing approximately 5% of thestate's population, exceeds the official COVID-19 death count for the entire state of Gujarat, even beforethe delta wave of the pandemic in India peaked in May 2021.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798819381816Subjects--Topical Terms:

1002712
Biostatistics.
Subjects--Index Terms:

COVID-19Index Terms--Genre/Form:

542853
Electronic books.

Statistical Methods for Mortality and Mobility Estimation after Natural Disasters.
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