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Population Density and Policy are Significant Drivers of Excess Deaths


Some states with low population density have similar levels of excess deaths than urban states

Since SARS-CoV2 (the virus that causes COVID-19) is an airborne disease, a state with a greater population density (people per squared mile) is more likely to have higher excess deaths because crowded spaces increase transmission and hospitals become overcrowded faster. Thus, more urban states are more likely to have a higher level of excess deaths than more rural states. The source of population density data by state is the US Census bureau.

The graph below shows the association between population density and the average weekly excess deaths per 100k since the start of the pandemic. In the chart, states like New Jersey, Rhode Island, Massachusetts, with relatively higher population densities, have higher average weekly excess mortality than more rural states like Arkansas and Wyoming. On the other hand, rural states like the Dakotas (SD & ND) and Mississippi have lower population densities but higher excess deaths.



A higher level of stringency in pandemic response policies is associated with lower average weekly excess deaths

The graph below shows the association between the average level of stringency in state policies since march 2020 and the average weekly excess deaths per 100k. The relationship between the variables observed is negative (albeit weakly as shown by the trendline). The graph shows that states like the Dakotas (ND & SD) had the least stringent policies in the US and some of the highest levels of weekly excess deaths per 100K people. In contrast, Hawaii, Maine and North Carolina had comparatively more stringent policies and lower excess mortality.

Oxford's COVID-19 Government Response Tracker aims to track and compare worldwide government responses to the coronavirus with a comparable metric. The index collects information on common policy responses and score the stringency of each measure through a comparison to normal times. The scores compound into an overall COVID-19 Government Response Stringency Index.

This COVID-19 Government Response Stringency Index is a composite measure that is a simple additive score of seven indicators, rescaled from 0 to 100. A score of 0 would correspond to policies in normal times and 100 is the highest level of restrictions. This measure is for comparative purposes only and should not be interpreted as a rating of the appropriateness or effectiveness of a state's response.

This webpage was developed by Harvard Kennedy School students for DPI-691M: Programming and Data for Policymakers.