The Annual Global Incidence Rate of Extreme Weather Event Disasters Appears Positively Correlated with World GDP, 1961-2020.

OBJECTIVE: This study compared the per capita annual global incidence rate of disasters caused by natural hazards with the annual world real gross domestic product, GDP (per global capita), as reported during 1961 through 2020. METHODS: Sixty (60) values for the world real GDP per global capita (in constant 2015 $USD) were compared to corresponding annual values for global incidence rates for five natural disaster subgroups and then for a total of twelve individual disaster types that comprise the subgroups; each expressed as an annual global incidence rate (in terms of annual incidence per 100,000 persons). Calculations of multiple linear regression, ANOVA, and Pearson's correlation coefficient were performed for comparing population-adjusted values for GDP to corresponding values. RESULTS: Four out of five hydrological and meteorological disasters were found to have a positive correlation with GDP. Results of the analysis revealed a relatively high degree of correlation between world GDP and the annual incidence of flood and storm disasters (P = 6.21 × 10-10 and P = 4.23 × 10-4, respectively). The annual incidence of heat waves and cold weather disasters also appeared to correlate with GDP (P = .002 and P = .019, respectively). In comparison, wet landslides indicated no such correlation (P = .862). No significant associations were found among the seven other individual biological, climatological, and geophysical disasters and GDP. CONCLUSION: The global incidence of four extreme weather (hydrometeorological) disasters appear to be positively associated with world real GDP during 1961-2020. These findings contradict previous postulates that the risk of disaster incidence is inversely associated with the capacity of the population.

Validity of the National Health Security Preparedness Index as a Predictor of Excess COVID-19 Mortality.

OBJECTIVE: This study compared 2019 values for the National Health Security Preparedness Index (NHSPI) with 2020 rates of coronavirus disease 2019 (COVID-19)-related mortality as reported by the 50 US states and Puerto Rico during the first six months of the US pandemic (March 1 - August 31, 2020). METHODS: Data regarding provisional death counts and estimates of excess deaths for COVID-19 according to state and territory were downloaded from the Centers for Disease Control and Prevention (CDC) National Center for Health Statistics website. Reporting included the six-month-long period of March 1 - August 31, 2020. Excess mortality rates were calculated as the number of excess deaths per 100,000 persons in each state population using 2019 US Census Bureau data. Mean values for state and territorial NHSPI domain indices were compared to state and territorial rates of COVID-19-related excess mortality using multiple linear regression, including analysis of variance. Correlations between the 51 state and territorial NHSPI values and corresponding COVID-19 excess mortality rates were calculated using Pearson's correlation coefficient. RESULTS: These calculations revealed a high degree of variance (adjusted r square = 0.02 and 0.25) and poor correlation (P = .16 and .08) among values for the overall NHSPI as compared to low and high estimates of excess COVID-19 mortality rates for 50 US states and Puerto Rico.There was also a high degree of variance (adjusted r square = 0.001 and 0.03) and poor correlation (P values ranging from .09 to .94) for values for the six individual domains of the NHSPI as compared to low and high estimates of excess COVID-19 mortality rates for 50 US states and Puerto Rico. CONCLUSION: The NHSPI does not appear to be a valid predictor of excess COVID-19 mortality rates for 50 US states and Puerto Rico during the first six months of the pandemic.