Kerala has a unique distribution of population among its towns and villages. On the one hand, the state lacks large cities—the largest, Thiruvananthapuram, had less than 800,000 people in 2011 and is the only 59th largest in India. At the other extreme, the state lacks small agglomerations as well, with only six villages having a population of less than 1,000. In comparison, neighbouring Tamil Nadu, whose population is a little more than double that of Kerala, has 5,000 villages with a population of less than 1,000. 

In the wake of the recent floods, this unique population distribution would have been both a boon and a bane for rescue and relief operations. 

Without large cities, operations would have to be more spread out across the state, and the challenges presented by towns and villages would have slowed rescue and relief operations. On the other hand, that there are no small agglomerations would have decreased the chances of a handful of people being stuck in otherwise uninhabited and remote areas, making it easier for rescue and relief teams to reach the entire population. 

There are several methods by which we can quantify the way the population in a state is distributed across towns and villages. Kerala stands apart, and by a long way from any other state in India. We will start by comparing the population distribution in Kerala with that of neighbouring Tamil Nadu and Karnataka, and states that have a similar population (Assam, Jharkhand and Odisha). In order to see the distributions clearly, we will restrict our analysis to towns of population 100,000 or less.

Each bar in figure 1 shows the number of towns or villages in that population bucket, and it becomes very apparent that Kerala is very different from the other states in India. In most states, as the population decreases, the number of villages with that population range goes up (notice in the graphs above that for all other states, the bars are in decreasing order). This is exactly according to standard theories of network science and complex systems. 

Kerala, though, is very different. The most common town populations there are in the 13,000-16,000 range, with a precipitous drop on either side. 

Another way to visualize population distribution is by arranging towns or villages in decreasing order of population, and looking at what proportion of towns account for a certain proportion of population, and then drawing a graph. Figure 2 shows this population distribution for the same six states, and once again, it is clear that Kerala stands much apart from the rest. 

In other words, the largest 50% of towns and villages in Kerala account for 75% of the population. In neighbouring Karnataka, barely 20% of the towns and villages account for three-fourth of the population. In fact, if we extend this analysis to all states and look at the proportion of towns and villages that account for 75% of the population, we find that Kerala is some distance away from the nearest states. 

In Kerala, we need the top 51% of agglomerations to account for 75% of the population, while in the next state (Tripura), only 39% of the towns or village are required to account for 75%. Kerala requires 25% of its towns and villages to cover for 50% of the population, while Tripura, which is next, requires only 16%.

Finally, while the population tables say that about 53% of Kerala’s population lives in villages, the interesting thing about the state is that there is very little to distinguish between the towns and villages in the state in terms of population distribution. In most states, the average village has less than 10% of the population as the average town. For all of India, the average village (with population 751) has about 5% of the population of the average town (with population 14,596). By now, we might expect Kerala to be far from this norm, and it doesn’t fail to deliver —the average village in Kerala has a population that is 71% of the population of the average town in the state! 

The reasons why Kerala’s population is so uniquely distributed, in a manner that contradicts all theories of network science, can be left for another day.

For now, we can think about what this unique distribution means in terms of rebuilding the state following the devastating floods. 

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