In a short span of 1 year, COVID-19 has emerged as the largest-ever health crisis of the twenty-first century. With over 78 million infections and 1.7 million deaths attributable to it until 23rd December 2020, COVID-19 attributable deaths account for 2.9% of additional deaths worldwide [1, 2]. The global spread of COVID-19 infection and attributable mortality has been highly uneven among and within countries. With 18.6 million infections and 3,30,824 COVID-19 attributable deaths, the USA accounts for 23.8% of global infections and 19.2% of global deaths [1]. India, with over 10 million infected cases and 1,46,476 COVID-19 deaths, is the second-largest country with respect to the size of infection and is ranked third with respect to COVID-19 attributable deaths [1]. The actual number of infections in many countries, including India, remains underestimated due to the asymptomatic nature of the infection and inadequate testing and surveillance system.
As the COVID-19 infection continues to spread, an increasing number of studies have become available on the extent of infection, the associated risk factors, and the crude fatality ratio (CFR) with and without time lag, projecting deaths and estimating the loss of life expectancy, premature mortality, and YPLL across countries [3,4,5,6,7,8,9]. Findings suggest that the infection rate across populations is largely underestimated, while the CFR shows large variations across countries, geographies, and demographic characteristics. The demographic structure, availability of health care resources, and multimorbid conditions explain COVID-19 attributable deaths to a larger extent [3, 10,11,12,13,14]. In China, fever, dyspnea, and chest pain/discomfort have been the more common symptom among the deceased patients, while fever has the most common symptom among the surviving patients [3, 10]. Older adults, people with comorbidities, and men are more susceptible to COVID-19 fatality [11, 15].
Evidence suggests that people with the COVID-19 infection are more prone to many life-threatening morbidities and fatalities [11, 16]. A study conducted in Italy found that fatigue, dyspnea, joint pain, and chest pain were persistent among the recovered patients [16]. Studies have projected premature mortality and reduction in life expectancy due to the infection across countries [4, 8, 17, 18]. After a certain threshold level of COVID-19 prevalence, life expectancy starts decreasing. In North America, Europe, Latin America, and the Caribbean, life expectancy at birth has been estimated to have reduced by 1 year at 10% prevalence of infection [4]. The COVID-19 attributable mortality has the potential to reduce life expectancy in India, weekly and annual life expectancy at birth in Spain, and seasonal life expectancy in Italy [8, 17, 18]. Besides mortality, many studies are available on the vulnerability to the COVID-19 infection, and mental distress, and loss of livelihood due to the preventive measures for containing the virus [19, 20].
The spread of COVID-19 has been largely uneven across the states of India. With 123 million population (9% of India’s population), Maharashtra is the second most populous and urbanized state in the country. It is one of the more developed states and ranks high on the human development index [21]. However, Maharashtra is the worst affected state with respect to COVID-19 infections and mortality. Until 23rd December 2020, it had 1.9 million cases and 48,876 deaths due to COVID-19, accounting for 19% of total infections and 34% of all COVID-19 attributable deaths in the country [22]. The case-fatality ratio in the state is higher than the national average. It has been observed that the rapid community transmission of the virus in a short time has resulted in a higher incidence of the disease and deaths resulting from it and, consequently, has affected the life expectancy [12]. Many states, including Maharashtra, are now experiencing the second and the third waves of the COVID-19 pandemic. With the global literature hinting at the implications of COVID-19 for longevity, it becomes imperative to make a regional assessment of the same owing to the disproportionately high load of infections and deaths due to the pandemic in the region. This assessment involves premature mortality, with its consequential bearing on life expectancy, person-years of life lost, and disability-adjusted life years (DALY). With the age-specific load of the infection and fatalities, person-years of life lost offers an understanding into the skewed share of life lost during the productive years, which has implications not only for a macro assessment, but also for household-level micro assessment. Years of potential life lost (YPLL) is a summary measure of premature mortality that reflects the sum of years lost from a predefined age, such as standard life expectancy. A higher YPLL is indicative of premature mortality and contributes to the compression of life expectancy. DALY measures the disease burden of the population and consists of YPLL and Years Lived with Disability (YLD). DALY serves to understand the implications of differential severity of the disease for individuals conditioned by their age, sex, and any pre-disposed condition. In the context of the COVID-19 pandemic, estimating YPLL and DALY is appropriate as over two-thirds of deaths are under 70 years of age ‘a standard age for estimating YPLL’ [2]. Patients affected by COVID-19 have long-term health complications and are more likely to be morbid than non-COVID-19 patients [23]. In ultimate terms, the loss of life expectancy in a regional setting reflects the severity of the pandemic with sustained and periodic soaring of infection in the state. In this context, this paper examines the effect of COVID-19 on premature mortality, life expectancy, YPLL, and DALY in one of the worst affected states of India, Maharashtra.
Data and methods
Data for this paper was drawn from multiple sources. These include the Report of the Expert Committee on Population Projections, Sample Registration System (SRS) Statistical Report 2018, and other published sources. The population size and distribution for Maharashtra for the year 2020 were taken from the Report of the Expert Committee on Population Projections [24]. The age-specific death rates for the state for the year 2018 (latest available data) were taken from the SRS Statistical Report and labelled as death rate without the COVID-19 infection [25]. The COVID-19 confirmed cases and deaths by age group were taken from the Times of India reports, dated 7th December 2020 and 21st December 2020 [26, 27]. The total number of confirmed cases and deaths until 20th December 2020 for Maharashtra and India were taken from covid19india.org [22]. We redistributed the total deaths until 20th December 2020, as per the distribution of deaths for which age data was available (7th December 2020). Age-specific case fatality ratio (ASCFR) was computed from the given data.