A new Shoresh Institution study by Prof. Ayal Kimhi examined the differences in municipal infection rates between the 1st and 2nd Covid-19 waves in Israel by statistically controlling for the levels of various municipal socioeconomic characteristics.
The Shoresh Institution for Socioeconomic Research, headed by Professor Dan Ben-David, is an independent, non-partisan policy research center providing evidence-based analyses of Israel’s economy and civil society.
The study, reported by Shoresh on Monday, isolated the unique contribution of each municipal attribute to the differences in the infection rate between municipalities. For example, two factors often linked together, population density and the share of Haredim in the municipal population, account together for more than half of the differences in municipal infection rates in both pandemic waves in Israel. But Prof. Kimhi found that the unique contribution of each of these attributes differed greatly between the two waves.
The new study’s main findings and conclusions included the fact that while population density was the particularly dominant determinant in the first wave, the leading determinant of municipal infection rates in the second wave was the percentage of Haredim in the municipal population.
The higher the share of elderly persons in the municipality, the lower its infection rate in the second wave.
The higher the share of persons with academic degrees in the municipality, the lower its infection rate in the second wave.
Prof. Kimhi said in a statement: “While the spread of the virus during the first wave resulted mainly from objective factors such as population density, its proliferation during the second wave was due primarily to behavioral differences in the population. Adults and more educated persons apparently took better care of themselves during the second wave than during the first wave, while segments of the Haredi population remained oblivious to the laws and regulations. This highlights the importance of both explaining the social distancing directives and strictly enforcing them in order to curb the spread of the virus.”
The study (Explaining differences in municipal infection rates between 1st and 2nd Covid-19 waves in Israel) observes that the policy of social distancing that led to the end of the first wave of the Covid-19 pandemic in Israel was abandoned early, causing the second wave to hit the country long before other countries who adopted more measured and cautious policies. The intensity of Israel’s second wave was considerably greater than that of the first wave, bringing the relevant hospital departments very close to full capacity. This led to a second nationwide economic lockdown during the October Jewish holiday season, followed by a significant drop in infection rates.
Starting on Sunday this week, the increasing trend of infection rates has been declared by the Israeli government to be a full third wave, resulting in a third lockdown.
In Kimhi’s empirical analysis focusing on the characteristics of infection rates during the first wave, it was found that differences in infection rates between municipalities with the highest infection rates and municipalities with the lowest infection rates were due to two main attributes: percentage of residents living in religious boarding schools, and population density (residents per square kilometer of a residential area). While population density can be considered an uncontrollable infection factor in the short-term, the fact that the Covid-19 virus infection rates were positively related to the percentage of residents living in religious boarding schools may indicate behavioral factors such as non-compliance with social distancing guidelines.
The study concludes that while the Israeli government’s “traffic light policy” implemented policy measures according to the changes in actual infection rates, policy measures may be much more effective if they are implemented even before there is an increase in infection rates, based on the characteristics of the municipalities that are prone to high infection rates.
The study suggests an inherent problem in analyzing the data on the number of infections in Israel is that they depend on the number of tests performed in each municipality, and those numbers are not random, meaning that they depend on each population group’s willingness to be tested. And as long as the tests are not mandatory, there is no escaping a bias in the resulting analysis.
In the end, the takeaway from the Shoresh study appears to be that a community’s willingness to obey government regulations regarding the pandemic inevitably determines the pace of its recovery and the avoidance of recurring infections.