Constructing a Spatial Public Service Availability Index (PSAI) for a Developing-Country Context: Development and Spatial Application in Bangladesh

In the modern world, a person's life chances are often shaped by the map they are born on. A child in one town might have a school down the street and a hospital nearby, while a child in another, perhaps only a few miles away, faces a long walk to the nearest clinic and no reliable power for their home. This uneven distribution of public services—things like education, healthcare, roads, and utilities—is a central challenge for governments trying to build fair societies. Measuring this inequality is difficult because services come in different forms: some are counted by the number of buildings, others by the length of roads, and others by the percentage of homes with a connection. To understand the full picture, researchers must combine these different types of data into a single, clear score that allows them to compare one place with another. This is the task of creating a composite index, a tool that turns a complex web of facts into a simple ranking, helping planners see where help is needed most.

A team of researchers from Khulna University in Bangladesh has taken on this challenge to map the availability of public services across their entire country. They focused on the 64 administrative districts of Bangladesh, a nation where population density and geography vary wildly, from the crowded capital to remote, hilly border regions. The researchers wanted to move beyond looking at just one sector, like electricity or water, in isolation. Instead, they built a new tool called the Public Service Availability Index. This index looks at six distinct areas: education, healthcare, transportation, electricity, gas supply, and water supply. By gathering data from the national census and open-source digital maps, they created a score for every district that reflects how many facilities and connections exist relative to the number of people living there. The goal was not to measure how good the services are, but simply to measure how many are available on the ground.

The process began by collecting raw numbers for each district. For schools, hospitals, and railway stations, the team counted how many existed and divided that number by the district's population to get a rate per person. For roads and railways, they measured the total length and divided it by the area of the district to see how dense the network was. For household utilities like electricity, gas, and water, they used the percentage of homes with a connection. Because these numbers come in different units and scales, the researchers used a standard method to level the playing field. They took the lowest value found in any district and set it to zero, and the highest value to one, stretching all the other districts' scores to fit between those two points. This allowed them to add the scores from all six categories together. They treated each category as equally important, giving them the same weight in the final calculation.

When the dust settled, the results painted a picture of stark inequality. The scores for the 64 districts ranged from a low of 0.451 to a high of 5.598. The district of Dhaka, the capital, held the top spot with a score of 5.598, reflecting strong performance across almost all categories. At the other end of the spectrum was Rangamati, a district in the hilly southeast, with the lowest score of 0.451. The average score across the country was 1.975. What made the findings particularly interesting was that a high overall score did not always mean a district was well-off in every way. For instance, the district of Bagerhat ranked third highest overall, but it had no recorded gas supply at all; its high rank was driven by excellent healthcare and education scores. Similarly, Narayanganj ranked sixth, despite having very low scores for education and healthcare, because it had high levels of gas and water connections. This showed that a single number could hide a very different reality depending on which services were strong and which were missing.

The study also revealed that some services were widespread while others were rare. Electricity was available to nearly all households in most districts, with an average coverage of nearly 96 percent. In contrast, piped gas and piped water were available to very few people, with average coverage of only about 6 percent and 5 percent respectively. This meant that a district could look very well-served if judged only by its electricity grid, but appear severely deprived if judged by its access to gas or water. The researchers found that gas and water supplies were highly correlated, meaning they tended to appear together in the same districts, and education and healthcare were also closely linked. However, transportation networks did not necessarily align with schools or hospitals; some districts had dense road networks but few educational institutions, and vice versa.

When the researchers looked at the map to see if these high-scoring districts were clustered together, the results were subtle. They used a statistical method to check if districts with similar scores were neighbors. The analysis suggested a weak tendency for high-scoring districts to group together near the center of the country, around the capital. However, this pattern was not strong enough to be considered a definitive national trend. After applying a strict correction to rule out random chance, only two districts stood out as having a statistically significant cluster status: one in the central region that was surrounded by other high-scoring neighbors, and another in the southeast that was a high-scoring island surrounded by lower-scoring areas. The rest of the country did not show a clear, consistent pattern of clustering. This suggests that while the capital region is a hub of service availability, the rest of the country does not follow a simple core-and-edge structure.

The researchers were careful to note the limits of their work. The index measures what is recorded on maps and in census tables, not the quality of the service or how easy it is for a person to actually reach it. A mapped hospital counts the same as a fully staffed one, and a road counts even if it is unpaved. Furthermore, the data came from different times, with population figures from 2022 and map data from around 2025, so the index is a hybrid snapshot rather than a single moment in time. There were also gaps in the data, such as missing records for some colleges and railway stations in certain districts, which the researchers treated as zeros but acknowledged might reflect data errors rather than a total lack of services. Despite these limitations, the study provides a transparent and reproducible way to compare districts. It shows that while some areas like Dhaka are well-connected across the board, others face specific, isolated shortages. The index serves not as a final verdict on a district's quality of life, but as a starting point for planners to investigate exactly which services are missing and where they need to be built.