<p><div><div><div><div data-show-faces="false" data-height="21" data-width="100" data-layout="button_count" data-send="true" data-href="https://www.r-bloggers.com/how-many-deaths-were-caused-by-the-hurricane-in-puerto-rico/"></div></div><div></div></div><div></div></div>
<div>
(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2018/09/mortality-in-puerto-rico.html"> Revolutions</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<div>
<p>President Trump is once again causing distress by <a rel="nofollow" href="https://twitter.com/realDonaldTrump/status/1040217897703026689" target="_blank">downplaying the number of deaths</a> caused by Hurricane Maria's devastation of Puerto Rico last year. Official estimates initially put the death toll at 15 before raising it to 64 months later, but it was <a rel="nofollow" href="https://www.vox.com/2018/9/13/17855414/trump-hurricane-maria-puerto-rico-death-toll" target="_blank">clear even then</a> that those numbers were absurdly low. The government of Puerto Rico <a rel="nofollow" href="https://prstudy.publichealth.gwu.edu/sites/prstudy.publichealth.gwu.edu/files/reports/Acertainment%20of%20the%20Estimated%20Excess%20Mortality%20from%20Hurricane%20Maria%20in%20Puerto%20Rico.pdf" target="_blank">commissioned an official report</a> from the Millikan Institute of Public Health at George Washington University (GWU) to obtain a more accurate estimate, and with its interim publication <a rel="nofollow" href="https://edition.cnn.com/2018/08/28/health/puerto-rico-gw-report-excess-deaths/index.html" target="_blank">official toll stands at 2,975</a>. </p>
<p>Why were the initial estimates so low? I read the interim GWU report to find out. The report itself is clearly written, quite detailed, and composed by an expert team of social and medical scientists, demographers, epidemiologists and biostatisticians, and I find its analysis and conclusions compelling. (Sadly however the code and data behind the analysis have not yet been released; hopefully they will become available when the final report is published.) In short:</p>
<ul>
<li>In the earliest days of the hurricane, the death-recording office was closed and without power, which suppressed the official count.</li>
<li>Even once death certificates were collected, it became clear that officials throughout Puerto Rico has not been trained on how to record deaths in the event of a natural disaster, and most deaths were not attributed correctly in official records. </li>
</ul>
<p>Given these deficiencies in the usual data used to calculate death tolls (death certificates) the GWU team used a different approach to calculate the death toll. The basis of the method was to estimate <strong>excess mortality</strong>, in other words, how many deaths occurred in the post-Maria period compared to the number of deaths that would have been expected if it had never happened. This calculation required two quantitative studies:</p>
<ul>
<li>An estimate of what the population would have been if the hurricane hadn't happened. This was based on a GLM model of monthly data from the prior years, accounting for factors including recorded population, normal emigration and mortality rates.</li>
<li>The total number of deaths in the post-Maria period, based on death certificates from the Puerto Rico government (irrespective of how the cause of death was coded).</li>
<li>(A third study examined the communication protocols before, during and after the disaster. This study did not affect the quantiative conclusions, but formed the basis of some of the report's recommendations.)</li>
</ul>
<p>The difference between the actual mortality, and the estimated &quot;normal&quot; mortality formed the basis for the estimate of excess deaths attributed to the hurricane. You can see those estimates of excess deaths one month, three months, and five months after the event in the table below; the last column represents the current official estimate.</p>
<p><a rel="nofollow" href="http://revolution-computing.typepad.com/.a/6a010534b1db25970b022ad36b1f3c200c-pi" target="_blank"><img border="0" alt="Excess mortality" title="Excess mortality" src="http://revolution-computing.typepad.com/.a/6a010534b1db25970b022ad36b1f3c200c-800wi"></a></p>
<p>These results are consistent in scale with another earlier study by <a rel="nofollow" href="https://www.nejm.org/doi/full/10.1056/NEJMsa1803972" target="_blank">Nishant Kishore et al</a>. (The data and R code behind this study is <a rel="nofollow" href="https://github.com/c2-d2/pr_mort_official" target="_blank">available on GitHub</a>.) This study attempted to quantify deaths attributed to the hurricane directly, by visiting 3299 randomly chosen households across Puerto Rico. At each household, inhabitants were asked about any household members who had died and their cause of death (related to or unrelated to the hurricane), and whether anyone had left Puerto Rico because of the hurricane. From this survey, the paper's authors extrapolated the number hurricane-related deaths to the entire island. The headline estimate of 4,625 at three months is somewhat larger than the middle column of the study above, but due to the small number of recorded deaths in the survey sample the 95% confidence interval is also much larger: 793 to 8498 excess deaths. (<a rel="nofollow" href="https://andrewgelman.com/2018/06/01/data-code-study-puerto-rico-deaths/" target="_blank">Gelman's blog</a> has some good discussion of this earlier study, including some commentary from the authors.)</p>
<p>With two independent studies reporting excess deaths well into the thousands attributable directly to Hurricane Maria, it's a fair question to ask whether a more effective response before and after the storm could have reduced the scale of this human tragedy.</p>
<p>Milken Institute School of Public Health: <a rel="nofollow" href="https://prstudy.publichealth.gwu.edu/" target="_blank">Study to Estimate the Excess Deaths from Hurricane Maria in Puerto Rico</a></p>
</div>
	<p>
<div>
<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="http://blog.revolutionanalytics.com/2018/09/mortality-in-puerto-rico.html"> Revolutions</a></strong>.</div>
<hr>
<a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers.com</a> offers <strong><a rel="nofollow" href="https://feedburner.google.com/fb/a/mailverify?uri=RBloggers">daily e-mail updates</a></strong> about <a rel="nofollow" href="https://www.r-project.org/" title="The R Project for Statistical Computing">R</a> news and <a rel="nofollow" href="https://www.r-bloggers.com/search/tutorial" title="R tutorials">tutorials</a> on topics such as: <a rel="nofollow" href="https://www.r-bloggers.com/search/data%20science" title="Data science">Data science</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/Big%20Data" title="Big Data">Big Data, <a rel="nofollow" href="https://www.r-users.com/" title="R jobs">R jobs</a>, visualization (<a rel="nofollow" href="https://www.r-bloggers.com/search/ggplot2" title="ggplot and ggplot2 tutorials">ggplot2</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/boxplot" title="Boxplots using lattice and ggplot2 tutorials">Boxplots</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/map" title="Maps and gis">maps</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/animation" title="Animation in R">animation</a>), programming (<a rel="nofollow" href="https://www.r-bloggers.com/search/RStudio" title="RStudio IDE for R">RStudio</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/sweave" title="Sweave and literate programming">Sweave</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/LaTeX" title="LaTeX in R">LaTeX</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/SQL" title="SQL and databases">SQL</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/eclipse" title="Eclipse IDE for R">Eclipse</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/git" title="git and github, Version Control System">git</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/hadoop" title="Large data in R using Hadoop">hadoop</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/Web+Scraping" title="Web Scraping of google, facebook, yahoo, twitter and more using R">Web Scraping</a>) statistics (<a rel="nofollow" href="https://www.r-bloggers.com/search/regression" title="Regressions and ANOVA analysis tutorials">regression</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/PCA" title="principal component analysis tutorial">PCA</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/time+series" title="Time series">time series</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/trading" title="finance trading">trading</a>) and more...
<img width="1" alt="" src="http://feeds.feedburner.com/~r/RBloggers/~4/FaKdwAeBZpg" height="1"></a></div>