Mortality risk within counterfactual models: Puerto Rico and Hurricane Maria
Authors: Jeffrey T Howard, Alexis R Santos-Lozada
Journal: The Lancet Planetary Health (2019)

Using data from the Puerto Rico Vital Statistics System obtained from the materials provided by Carlos Santos-Burgoa and colleagues,1Santos-Burgoa C Sandberg J Suárez E et al.Differential and persistent risk of excess mortality from Hurricane Maria in Puerto Rico: a time-series analysis.Lancet Planet Health. 2018; 2: 478-488Summary Full Text Full Text PDF Scopus (101) Google Scholar we compared the census-based and displacement models with death counts for Puerto Rico for the period after Hurricane Maria. We calculated confidence intervals for deaths from 2010 to 2016 for observed deaths (figure) and compared them with the pre-Hurricane and post-Hurricane counts (2017) and both counterfactual models. The displacement model falls outside of the pattern observed over the past 7 years before Hurricane Maria, while mortality between January and August does not (figure). A comparison of the upper limits of the historical 95% and 99% CIs produced estimates of excess deaths of 1061 and 985, which are consistent with the census-based model1Santos-Burgoa C Sandberg J Suárez E et al.Differential and persistent risk of excess mortality from Hurricane Maria in Puerto Rico: a time-series analysis.Lancet Planet Health. 2018; 2: 478-488Summary Full Text Full Text PDF Scopus (101) Google Scholar and previous estimates.2Santos-Lozada AR Howard JT Use of death counts from vital statistics to calculate excess deaths in Puerto Rico following Hurricane Maria.J Am Med Assoc. 2018; 320: 1491-1493Crossref Scopus (63) Google Scholar Even though the predicted number of deaths in the displacement model was less than the historical ranges, it was the only estimate provided to the Government of Puerto Rico.3Andrade E Barrett N Colon-Ramos U et al.Ascertainment of the estimated excess mortality from Hurricane Maria in Puerto Rico. August 28, 2018. Milken Institute School of Public Health, Washington, DC2018https://prstudy.publichealth.gwu.edu/Date accessed: April 16, 2019Google Scholar If death counts before Hurricane Maria fell within historical ranges, why is this outcome not the case for the counterfactual model? A counterfactual model is supposed to represent what would have been expected if an event did not occur, so why would the preferred counterfactual model include additional hurricane-induced population displacement? In addition, the only way this model would occur is by assuming higher mortality risk for those who were displaced than for those who stayed behind. This assumption ignores the selectivity mechanisms that operate after climate disasters regarding population mobility. Previous research, albeit in other contexts, has found that those who remain behind have characteristics associated with higher mortality risk.4Thiede BC Brown DL Hurricane Katrina: Who stayed and why?.Popul Res Policy Rev. 2013; 32: 804-824Crossref Scopus (47) Google Scholar The displacement model overstates the mortality risk for those who were displaced with a mortality rate ratio of 158 in comparison with the census-based model or 165 compared with the displacement model.5Santos-Lozada AR Howard JT Supplement to: ascertaining mortality risk within counterfactual models: Puerto Rico and Hurricane Maria. GitHub.https://alexisrsantos.github.io/Correspondence_Lancet/Date: 2018Date accessed: April 10, 2019Google Scholar Assuming a higher mortality risk for displaced individuals seems to contradict other findings within the Article,1Santos-Burgoa C Sandberg J Suárez E et al.Differential and persistent risk of excess mortality from Hurricane Maria in Puerto Rico: a time-series analysis.Lancet Planet Health. 2018; 2: 478-488Summary Full Text Full Text PDF Scopus (101) Google Scholar which shows a higher risk for individuals of an older age and lower socioeconomic status—ie, those who are less likely to migrate.4Thiede BC Brown DL Hurricane Katrina: Who stayed and why?.Popul Res Policy Rev. 2013; 32: 804-824Crossref Scopus (47) Google Scholar Estimates produced after Hurricane Maria have gravitated around 1000 excess deaths. A meta-analysis5Santos-Lozada AR Howard JT Supplement to: ascertaining mortality risk within counterfactual models: Puerto Rico and Hurricane Maria. GitHub.https://alexisrsantos.github.io/Correspondence_Lancet/Date: 2018Date accessed: April 10, 2019Google Scholar of previous estimates produced with vital statistics points towards a figure of 1093 (95% CI 943–1242). Excess death estimates comparing the observed deaths between September, 2017, and February, 2018, and the upper limit of the historical confidence intervals, are within the margins of the census-based model1Santos-Burgoa C Sandberg J Suárez E et al.Differential and persistent risk of excess mortality from Hurricane Maria in Puerto Rico: a time-series analysis.Lancet Planet Health. 2018; 2: 478-488Summary Full Text Full Text PDF Scopus (101) Google Scholar and previous estimates.2Santos-Lozada AR Howard JT Use of death counts from vital statistics to calculate excess deaths in Puerto Rico following Hurricane Maria.J Am Med Assoc. 2018; 320: 1491-1493Crossref Scopus (63) Google Scholar The census model captured all the previous estimates, produced before the publication of the Article, within its 95% CI.5Santos-Lozada AR Howard JT Supplement to: ascertaining mortality risk within counterfactual models: Puerto Rico and Hurricane Maria. GitHub.https://alexisrsantos.github.io/Correspondence_Lancet/Date: 2018Date accessed: April 10, 2019Google Scholar The outlier is the estimate derived from the displacement model; surprisingly, this estimate was the only one provided to the Government of Puerto Rico.3Andrade E Barrett N Colon-Ramos U et al.Ascertainment of the estimated excess mortality from Hurricane Maria in Puerto Rico. August 28, 2018. Milken Institute School of Public Health, Washington, DC2018https://prstudy.publichealth.gwu.edu/Date accessed: April 16, 2019Google Scholar We declare no competing interests. Mortality risk within counterfactual models: Puerto Rico and Hurricane Maria – Authors' replyThe main argument by Jeffrey Howard and Alexis Santos-Lozada appears to be that because the predicted number of deaths from the displacement model in our analysis was lower than historical averages and previous counterfactual estimates for the period after Hurricane Maria, this estimate, and estimates of excess mortality associated with them therefore must be biased or inaccurate in some way. The opposite is in fact the case. It is estimates of excess mortality that ignore displacement that are biased. Full-Text PDF Open AccessDifferential and persistent risk of excess mortality from Hurricane Maria in Puerto Rico: a time-series analysisAnalysis of all-cause mortality with vital registration data allows for unbiased estimation of the impact of disasters associated with natural hazards and is useful for public health surveillance. It does not depend on certified cause of death, the basis for the official death toll in Puerto Rico. Although all sectors of Puerto Rican society were affected, recovery varied by municipal socioeconomic development and age groups. This finding calls for equitable disaster preparedness and response to protect vulnerable populations in disasters. Full-Text PDF Open Access