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Assuming that appropriate steps are taken to anonymize and aggregate these data streams in secure ways, novel data streams offer ways to assess the needs of populations more accurately ( 9, 10). These data, such as flight information, mobile phone data, or social media traces, can provide insight into the fluctuation of their respective populations at a high temporal and geographic resolution, both before and after a disaster. In an increasingly digitally connected world, however, passively collected digital records are often maintained by technological services providers for billing or marketing purposes. Rapid censuses conducted in short intervals before and after a disaster are both logistically and financially impractical. New approaches to estimating fluctuating denominators in near real time would greatly improve disaster response and the assessment of local needs in the short- and long-term aftermath. In the absence of reliable migration data in the wake of natural disasters, the population size estimate used by government agencies and researchers generally relies on census estimates and assumes a linear change in population size between intervals or a constant population size since the most recent estimate ( 7, 8). Passively collected data provide a promising supplement to current at-risk population estimation procedures however, each data source has its own biases and limitations. Finally, our analysis measures a general shift of population from rural to urban centers within the island. Moreover, we infer that these municipalities experienced greater infrastructure damage as measured by the proportion of unknown locations stemming from these regions. On average, municipalities with a smaller population size lost a bigger proportion of their population. Census data predict a population loss of just over 129,000 from July 2017 to July 2018, a 4% decrease air travel data predict a population loss of 168,295 for the same period, a 5% decrease mobile phone-based estimates predict a loss of 235,375 from July 2017 to May 2018, an 8% decrease and social media-based estimates predict a loss of 476,779 from August 2017 to August 2018, a 17% decrease. We observed a loss of population across all data sources throughout the study period however, the magnitude and dynamics differ by the data source. We compared these two data sources with population estimates derived from air travel records and census data.
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Here, we analyzed data generated by mobile phones and social media to estimate the weekly island-wide population at risk and within-island geographic heterogeneity of migration in Puerto Rico after Hurricane Maria. Measuring this displacement is vital for both optimal postdisaster resource allocation and calculation of measures of public health interest such as mortality estimates. Population displacement may occur after natural disasters, permanently altering the demographic composition of the affected regions.