Measuring COVID-19 vaccination coverage: an enhanced age-adjusted two-step floating catchment area model

Abstract

Background There are only limited studies on access to COVID-19 vaccines and identifying the most appropriate health centres for performing vaccination in metropolitan areas. This study aimed to measure potential spatial access to COVID-19 vaccination centres in Mashhad, the second-most populous city in Iran. Methods The 2021 age structure of the urban census tracts was integrated into the enhanced two-step floating catchment area model to improve accuracy. The model was developed based on three different access scenarios: only public hospitals, only public healthcare centres and both (either hospitals or healthcare centres) as potential vaccination facilities. The weighted decision-matrix and analytic hierarchy process, based on four criteria (i.e. service area, accessibility index, capacity of vaccination centres and distance to main roads), were used to choose potential vaccination centres looking for the highest suitability for residents. Global Moran’s index (GMI) was used to measure the spatial autocorrelation of the accessibility index in different scenarios and the proposed model. Results There were 26 public hospitals and 271 public healthcare centres in the study area. Although the exclusive use of public healthcare centres for vaccination can provide the highest accessibility in the eastern and north-eastern parts of the study area, our findings indicate that including both public hospitals and public healthcare centres provide high accessibility to vaccination in central urban part. Therefore, a combination of public hospitals and public healthcare centres is recommended for efficient vaccination coverage. The value of GMI for the proposed model (accessibility to selected vaccination centres) was calculated as 0.53 (Z = 162.42, P < 0.01). Both GMI and Z-score values decreased in the proposed model, suggesting an enhancement in accessibility to COVID-19 vaccination services. Conclusions The periphery and poor areas of the city had the least access to COVID-19 vaccination centres. Measuring spatial access to COVID-19 vaccination centres can provide valuable insights for urban public health decision-makers. Our model, coupled with geographical information systems, provides more efficient vaccination coverage by identifying the most suitable healthcare centres, which is of special importance when only few centres are available. Graphic abstract

Inequality in the distribution of Covid-19 vaccine: a systematic review

“…In other words, people who were unemployed had a lower vaccination rate [ 39 ]. Other economic factors affecting the lack of access to Covid-19 vaccine were poverty [ 36 , 43 ] and living in deprived areas [ 45 , 47 – 49 ]. Vaccination rates were also lower in people with limited access to healthy food [ 39 ].…”

Spatial epidemiology of COVID-19 infection through the first outbreak in the city of Mashhad, Iran

“…It should be noted that the most effective way to deal with this highly contagious disease is universal and integrated vaccination. Vaccination against the disease has been able to greatly cut down the hospitalization and fatality rates of COVID-19 [ 30 ].…”

A geographical information system model to define COVID-19 problem areas with an analysis in the socio-economic context at the regional scale in the North of Spain

“…Geospatial sciences play a strategic role in shortening response times for pandemic management (Zhou et al, 2020) and planning measures according to spatial models of key topics, such as incidence ratios, hotspot setting and even accessibility to healthcare centres (Mohammadi et al, 2021). Along with this thinking, we previously developed a geoprevention approach based on models to control the virus spread (De Cos et al, 2021b).…”