Background: Urban poor face a disproportionate burden of ill health and high out-of-pocket expenditure (OOPE), creating a severe unmet need for affordable and quality health care. This article highlights the impact of health insurance on OOPE and catastrophic healthcare expenditure among the urban poor of India. Methods: The study uses randomly collected household data from a baseline survey conducted in the states of Rajasthan and Uttar Pradesh. Separate Insurance impact models have been generated for the analysis. Results: Mean out-of-pocket health expenses is higher in the private health facility for the inpatient care but in case of outpatient care, the expenditure was more in public. Expenditure on medicine constitutes the largest part of the total OOPE. Insurance impact model shows that coverage on medicine alone can reduce medical impoverishment by 85% in the case of Outpatient Deparment (OPD) and 71% in the case of Inpatient Department (IPD). The urban poor preferred private facility for treatment in case of illness, albeit when it comes to delivery, they prefer public facility Conclusions: Study findings indicate overt reliance on private health care must be regulated, to reduce OOPE among the urban poor. Also, effective universal health insurance can go a long way in reducing the OOPE with availability of free medicines and diagnostics in the public health facilities.

Vaccination is a potential public health solution for the prevention of infection. It reduces the severity of symptoms in case of COVID-19. Despite the availability of vaccines, some people are hesitant to be vaccinated. The objectives of the study were to measure the proportion of vaccine hesitancy among the peri-urban population and identify its determinants. An adult population of 303 from two peri-urban areas in the field practice area of Urban Health Training Centre, Rama Medical College were interviewed from 22nd February 2021 to 25th March 2021. Epicollect 5 was used for collecting data and STATA 16 was used for analysis. Multivariable logistic regression was applied to compute the adjusted odd ratio (95% confidence interval) to find out the determinants of vaccine hesitancy. Three Cs model guided tools of data collection and analyses. More than one fourth (28%) of the participants were vaccine-hesitant whereas 34.6% of participants had no confidence in the vaccine. Other reasons were complacency (40.6%) and convenience (35.9%). Vaccine hesitancy was significantly associated with gender [AOR = 2.40 (1.12-5.16)] and trust in government [AOR = 0.18 (0.08-0.45)] but no association with age group, political affiliation and source of information about the vaccine.  It is important to build the trust of people in vaccines, make it convenient and resolve the issues that are making them complacent. The health system needs to involve non-governmental organisations to reach out to those for whom there are issues of availability and approach.