Household catastrophic health expenditure for COVID-19 during March-August 2021, in South India: a cross-sectional study.

BACKGROUND: The Coronavirus disease 2019 (COVID-19) pandemic increased the utilisation of healthcare services. Such utilization could lead to higher out-of-pocket expenditure (OOPE) and catastrophic health expenditures (CHE). We estimated OOPE and the proportion of households that experienced CHE by conducting a cross-sectional survey of 1200 randomly selected confirmed COVID-19 cases. METHODS: A cross-sectional survey was conducted by telephonic interviews of 1200 randomly selected COVID-19 patients who tested positive between 1 March and 31 August 2021. We collected household-level information on demographics, income, expenditure, insurance coverage, direct medical and non-medical costs incurred toward COVID-19 management. We estimated the proportion of CHE with a 95% confidence interval. We examined the association of household characteristics; COVID-19 cases, severity, and hospitalisation status with CHE. A multivariable logistic regression analysis was conducted to ascertain the effects of variables of interest on the likelihood that households face CHE due to COVID-19. RESULTS: The mean (95%CI) OOPE per household was INR 122,221 (92,744-1,51,698) [US$1,643 (1,247-2,040)]. Among households, 61.7% faced OOPE, and 25.8% experienced CHE due to COVID-19. The odds of facing CHE were high among the households; with a family member over 65 years [OR = 2.89 (2.03-4.12)], with a comorbid individual [OR = 3.38 (2.41-4.75)], in the lowest income quintile [OR = 1.82 (1.12-2.95)], any member visited private hospital [OR = 11.85 (7.68-18.27)]. The odds of having CHE in a household who have received insurance claims [OR = 5.8 (2.81- 11.97)] were high. Households with one and more than one severe COVID-19 increased the risk of CHE by more than two-times and three-times respectively [AOR = 2.67 (1.27-5.58); AOR = 3.18 (1.49-6.81)]. CONCLUSION: COVID-19 severity increases household OOPE and CHE. Strengthening the public healthcare and health insurance with higher health financing is indispensable for financial risk protection of households with severe COVID-19 from CHE.

Emotions in the time of COVID-19: A sentiment analysis of tweets during the nationwide lockdown in India (preprint)

Background: COVID-19 pandemic is unprecedented in terms of burden, nature and quantum of control measures and public reactions. We report trends in public emotions and sentiments before and during the nation-wide lockdown implemented since 25th March 2020 in India. Methods: We collected a sample of tweets containing the keywords 'coronavirus' or 'COVID-19' published between 12th March and 14th April in India. After pre-processing, the tweets were subjected to sentiment analysis using natural language processing algorithms. Results: Our analysis of 226170 tweets revealed a positive public sentiment (mean sentiment score=0.25). Tweets expressing a given sentiment showed significant (p<0.001) waning of negativity; negative tweets decreased (39.3% to 35.9%) and positive tweets increased (49.8% to 51.8%). Trust (0.85 words/tweet/day) and fear (0.66 words/tweet/day) were the dominant positive and negative emotions, respectively. Conclusions: Positive sentiments dominated during the COVID-19 lockdown in India. A surveillance system monitoring public sentiments on public health interventions for COVID-19 should be established.

National sero-surveillance to monitor the trend of SARS-CoV-2 infection transmission in India: Protocol for community-based surveillance.

Conducting population-based serosurveillance for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) will estimate and monitor the trend of infection in the adult general population, determine the socio-demographic risk factors and delineate the geographical spread of the infection. For this purpose, a serial cross-sectional survey would be conducted with a sample size of 24,000 distributed equally across four strata of districts categorized on the basis of the incidence of reported cases of COVID-19. Sixty districts will be included in the survey. Simultaneously, the survey will be done in 10 high-burden hotspot cities. ELISA-based antibody tests would be used. Data collection will be done using a mobile-based application. Prevalence from the group of districts in each of the four strata will be pooled to estimate the population prevalence of COVID-19 infection, and similarly for the hotspot cities, after adjusting for demographic characteristics and antibody test performance. The total number of reported cases in the districts and hotspot cities will be adjusted using this seroprevalence to estimate the expected number of infected individuals in the area. Such serosurveys repeated at regular intervals can also guide containment measures in respective areas. State-specific context of disease burden, priorities and resources should guide the use of multifarious surveillance options for the current COVID-19 epidemic.