Geographical variation in case fatality rate and doubling time during the COVID-19 pandemic

Abstract

Case fatality rate (CFR) and doubling time are important characteristics of any epidemic. For coronavirus disease 2019 (COVID-19), wide variations in the CFR and doubling time have been noted among various countries. Early in the epidemic, CFR calculations involving all patients as denominator do not account for the hospitalised patients who are ill and will die in the future. Hence, we calculated cumulative CFR (cCFR) using only patients whose final clinical outcomes were known at a certain time point. We also estimated the daily average doubling time. Calculating CFR using this method leads to temporal stability in the fatality rates, the cCFR stabilises at different values for different countries. The possible reasons for this are an improved outcome rate by the end of the epidemic and a wider testing strategy. The United States, France, Turkey and China had high cCFR at the start due to low outcome rate. By 22 April, Germany, China and South Korea had a low cCFR. China and South Korea controlled the epidemic and achieved high doubling times. The doubling time in Russia did not cross 10 days during the study period.

Estimating the Case Fatality Ratio for COVID-19 using a Time-Shifted Distribution Analysis

“…However, it is instructive to calculate in this way, for any given country, the proportion of detected cases that are currently proving fatal, for the purposes of public health management and planning. For comparison, Mazumder and colleagues [8] calculated case fatality ratios for a range of countries using recovery and death [24]. Using the revised data, the TSD analysis provided an even more robust fit; the CFR was almost unchanged at 11% but the delay time was increased to 14 days.…”

“…Further, even once the distribution of times from onset of disease to death is known, it can be difficult to use this information to accurately correct the crude CFR. An alternative method is to use data for closed cases only, once patients have recovered or died (eg [7,8]), yet this information is also difficult to obtain during an outbreak and may be biased towards a particular demographic or 3 skewed by delays in reporting of recoveries. Other biases in calculating CFR include underascertainment of mild or asymptomatic cases, time lags in testing and reporting, and the effects of intervention approach, demographics and reporting schemes [9].…”

“…However, it is instructive to calculate in this way, for any given country, the proportion of detected cases that are currently proving fatal, for the purposes of public health management and planning. For comparison, Mazumder and colleagues [8] calculated case fatality ratios for a range of countries using recovery and death data from closed cases. They analysed eleven countries with high outcome rates and sufficient progression in the outbreak for analysis (at the end of April), but many of their calculated CFR values are much higher than our estimates — for example, estimated CFR above 30% for Italy, France and USA at the end of April — probably due to delays in recovery reporting, whereas estimated CFR values for Germany, China and South Korea match ours.…”

Weather Parameters and COVID-19

“…5 Weekly doubling time was calculated using the following equation: T d = ( t 2 – t 1 )log 2/log( q 2 / q 1 ), where q 1 and q 2 are the number of cases on time point 1 and 2, respectively and T d is doubling time. 6 Doubling time was evaluated against mean weekly temperature, wind speed and humidity. Pearson's correlation coefficient was used to examine the relationship between weather variables and daily COVID-19 cases.…”

Stock Prices, Lockdowns, and Economic Activity in the Time of Coronavirus

“…New COVID deaths per capita capture the current death rate but not the slope of its trajectory. To characterize the trajectory, we follow Mazumder et al (2020) and calculate the time it takes for accumulated cases to double, as measured by…”