Statistical approach
The utilisation of ANC services for pregnant women of second and third trimesters is examined. In the case of mothers under two years, these services are completed; hence, there are no exclusion criteria for the analysis. The trend of ANC service utilisation is based on three rounds of surveys, to show the impact of intervention. Authors analysed the involvement of community health workers like ASHAs, ANMs, and AWWs in creating awareness regarding ANC, providing counselling, and supporting women while seeking ANC during the pre and post-pandemic periods separately for PW and MU2(2018–19 and 2021–2022). ANOVA is used to understand the differentials in exposure and outcome variables by womens varying characteristics post-covidLastly, the role of the CHWs in utilising ANC by women was explored using bivariate analysis, and the impact of the services provided by the CHWs was analysed using the propensity score method (PSM). The matching technique was used because the beneficiaries were not randomly selected, as a result of which selection bias could be introduced in the estimated impact of the programme. The covariates matched in the present study encompassed categorical variables like caste, education, religion, type of house, and availability of land. The analysis was carried out in the following steps.Firstly, the logit model was used to estimate the propensity score for the covariates presenting mothers' demographic and socio-economic characteristics. Next, we used the k-match command to calculate the difference, known as the average treatment effect (ATE), in the utilisation of maternal health services between the control group (those who didn't receive or avail services through CHWs) and the treatment group (those who received assistance from the CHWs). The difference is presented in terms of proportion.There are basic assumptions that need to be satisfied for using PSM. The first is that the potential outcomes must be determined in a way that they are independent of the treatment assignment, possibly carried out by including all the covariates that affect the outcome or the treatment. The second is a common support or overlap condition; that is, the treatment units will have to be similar to control units in observed characteristics unaffected by the participation of CHWs. The data was collected using CS Pro (Census and survey processing system) and extracted and analysed using STATA 15.1.