Analysis of the COVID-19 testing parameters and progression of the pandemic at the district level: findings from the ICMR Hundred Million Test (HMT) database during the first wave in India

BACKGROUND

India had the second-highest number of COVID-19 cases globally. We evaluated the progression of the pandemic across the lockdowns and phased reopenings at the district level during the first wave (in India).

METHODS

For the analysis in this study, we used more than 100 million COVID-19 test results along with other parameters available in the Indian Council of Medical Research database from March 2020 to October 2020. The districts were stratified as high, moderate, and low caseload districts and data analysis was done for each phase of lockdown.

FINDINGS

Of the 110.5 million tests included in the analysis, 54.79 million tests were performed using molecular methods, 53.58 million by rapid antigen tests, and 2.13 million using the indigenous TruNat platform. The proportion of positive cases among symptomatic individuals (22.6%) was significantly higher than asymptomatic individuals (8.6%). The tests conducted and proportions of positivity were significantly higher in high caseload districts; 58% of these tests were conducted using molecular methods as opposed to only one-third in low caseload districts.

INTERPRETATION

Laboratory parameters, along with other demographic information, can help us better understand the spread of the pandemic in a country. This information can be crucial to formulating and implementing public health policies in future waves of the pandemic.

Serological survey for SARS-CoV-2 antibodies among tribal communities of Odisha post-second wave

Background & objectives

Serial national level serosurveys in India have provided valuable information regarding the spread of COVID-19 pandemic in the general population, but the impact of the ongoing pandemic on the tribal population in India is not well understood. In this study, we evaluated the seroprevalence of COVID-19 antibodies in the tribal population of Odisha post-second wave (September 2021).

Methods

A population-based, age-stratified, cross-sectional study design was adopted for the survey, carried out in seven tribal districts of Odisha from 30^th August to 16^th September 2021. A multistage random sampling method was used where serum samples were tested for antibodies against the SARS-CoV-2 nucleocapsid (N) protein in each district, and a weighted seroprevalence with 95 per cent confidence interval (CI) was estimated for each district.

Results

A total of 2855 study participants were included from the seven tribal districts of Odisha in the final analysis. The overall weighted seroprevalence was 72.8 per cent (95% CI: 70.1-75.3). Serological prevalence was the highest among 18-44 yr (74.4%, 95% CI: 71.3-77.3) and from Sambalpur district [75.90% (66.90-83.10)]. Among participants, 41.93 per cent had received at least one dose of any COVID-19 vaccine. Kandhamal district had the highest number of fully immunized participants (24.78%), and in Sundergarh district, most of the study participants (58.1%) were unimmunized.

Interpretation & conclusions

This study found high seroprevalence against SARS-CoV-2 in the tribal population of Odisha. The vaccination coverage is at par with the general population, and efforts to address some knowledge gaps may be needed to improve the coverage in the future.

Is multimorbidity associated with risk of elder abuse? Findings from the AHSETS study

BACKGROUND

With an increasing number of older adults in low- and middle-income countries (LMIC), the burden of multimorbidity and functional dependence is on the rise. At the same time, a higher prevalence of elder abuse is observed in these populations. There is scarce evidence on the interplay between elder abuse and multimorbidity with no reports from LMIC settings yet. Present study examined the association of multimorbidity with the risk of elder abuse and its correlates in a rural elderly population of Odisha, India.

METHODS

The data for this study was collected as a part of our AHSETS study comprising of 725 older adults residing in rural Odisha, India. Multimorbidity was assessed by the MAQ PC tool while Hwalek-Sengstock elder abuse screening test (HS-EAST) was used to assess the risk of elder abuse. Functional dependence was measured by the Lawton IADL questionnaire. We used ordinal logistic regression models to identify the correlates of elder abuse and test for mediation by functional dependence.

RESULTS

Around 48.8 % (95 % CI:45.13-52.53 %) older adults had multimorbidity while 33.8 % (95 % CI:30.35-37.35 %) had some form of dependence. Out of 725, 56.6 % (CI 52.85-60.19 %) were found to be at low-risk elder abuse and 15.9 % (CI 13.27-18.72 %) being at high-risk. The prevalence of higher risk of elder abuse was greater among females, non-literates, widowed persons, those not currently working and those belonging to lower socio-economic strata. The risk of elder abuse was significantly associated with multimorbidity (AOR = 1.68; 95 %CI: 1.11-2.57) and functional dependence (AOR = 2.08; 95 %CI: 1.41-3.06). Additionally, we found a partial mediation mechanism of functional dependency between the pathway of multimorbidity and elder abuse.

CONCLUSIONS

Elder abuse and multimorbidity are emerging as issues of significant concern among rural elderly in Odisha, India. Multimorbidity and functional dependence are associated with significantly higher odds of elder abuse among rural older adults. Further, we report the role of functional dependence as a partial mediator between multimorbidity and elder abuse. Therefore, potential interventions on reducing the economic, physical and care dependence among multimorbid patients may reduce the risk of elder abuse.

Prevalence and Patterns of Multimorbidity Among Rural Elderly: Findings of the AHSETS Study

Introduction: In India, the proportion of older population is projected to increase from 8% in 2015 to 19% in 2050 and a third of the country's population will be older adults by end of the century. Multimorbidity is common among the elderly and the prevalence increases with age. Chronic conditions are most often present as clusters and it's critical to explore the prevalent pattern of clustering for better public health strategies. Method: A cross-sectional study was conducted among 725 rural older adults (>60 years) in Tigiria block of Odisha, India. Multimorbidity status was assessed using the prior validated MAQ-PC tool. Survey was conducted using android tablets installed with open data kit software. While Euclidean distances using K-means clustering algorithm were used to estimate the similarity or dissimilarity of observations. The optimum numbers of clusters were determined using silhouette method. Data were analyzed using multiple open source packages of R statistical programming software ver-3.6.3. Result: The overall prevalence of multimorbidity was 48.8% of which dyads (25%) were the most common form, followed by triads (15.2%). The prevalence of multimorbidity was higher in females (50.4%) than males (47.4%). The optimal number of clusters was found to be 3. While arthritis alone was a separate cluster, hypertension and acid peptic disease were in another cluster and all the rest conditions were included in the third cluster. Conclusion: The cluster analysis to measure of proximity suggested arthritis, hypertension, and acid peptic disease are the diseases that occur mostly in isolation with the other chronic conditions in the rural elderly.