The infection fatality rate of Covid-19 is inversely proportional to testing: Study | Economic Times

MUMBAI: The infection fatality rate of Covid-19 is inversely proportional to testing, according to a new study, which can guide public health officials to expand testing criteria and help lower mortality.The study by MS Seshadri, medical director of Thirumalai Mission Hospital in Ranipet, and R Ranganathan of Coimbatore Institute of Technology is to be published in the International Journal of Community Medicine and Medical Health. It says that as India increased testing, the infection fatality rate fell. IFR is calculated as deaths due to an infection.However, Seshadri says that since deaths due to Covid-19 can take place one to four weeks after infection, the lag should be taken into account while calculating the IFR. Other factors that influence IFR, the authors say, are the percentage of positive cases identified by RT-PCR (reverse transcriptase polymerase chain reaction) tests, which may vary depending on the kits; mortality reporting rate or proportion of deaths certified by a medical practitioner, which may differ from country to country, be lower in rural than in urban areas, and the number of tests per million population per week.The more the number of tests done, the greater the number of asymptomatic subjects diagnosed with infection and lower the IFR. As India’s testing increased, the IFR also declined, indicating that public health officials were able to catch infected individuals early and isolate or started treatment of at-risk individuals early. “We found a statistically significant correlation on increased tests and reduced mortality,” Seshadri told ET. “A progressive increase in testing will detect more infections and so the denominator in the calculation of IFR increases and so the IFR will decline.”Seshadri suggested that India needs to start reporting cases on the basis of mortality to understand the true impact of the virus. Calculating IFR becomes essential as a steep rise in IFR can possibly overwhelm the healthcare system. It is important to compute this data to plan the requirement of ICU beds.