<mark>16.1. All cleaning, processing, and analysis was conducted by the research team and the code is available</mark><sup>_29_</sup> <mark>.</mark>

**<mark>Food Insecurity Experience Scale:</mark>** <mark>The estimates of prevalence of (i) moderate or severe and (ii) severe food insecurity among adult individuals are based on the eight-question Food Insecurity Experience Scale (FIES), which was included as a module in the high-frequency phone survey. The FIES is an experience-based metric of food insecurity severity, which relies on people’s direct responses to questions about their experiences with access to adequate food. This metric makes it possible to compare prevalence rates of food security across national and sub-national populations</mark><sup>_30_</sup> <mark>. Widely used around the world, FIES is an appropriate measure for assessing food security as it is a direct measure of food insecurity which produces comparable estimates of food insecurity experienced by people in different contexts.</mark>

<mark>In the high-frequency phone surveys that inform our analyses, the FIES questions had a reference period of the last 30 days. Following the FIES standard survey model, eight questions were asked, aimed to capture whether the respondent or other adult households members: (i) were worried they would not have enough to eat, (ii) were unable to eat healthy and nutritious food, (iii) ate only a few kinds of foods, (iv) had to skip a meal, (v) ate less than they thought they should, (vi) ran out of food, (vii) were hungry but did not eat, and (viii) went without eating for a whole day.</mark> <mark>The approach to process and analyze FIES data comes from Item Response Theory</mark><sup>_31_</sup> <mark>, also known as the Rasch model</mark><sup>_32_</sup> <mark>, which accounts for the measurement of unobservable traits through the analysis of responses to survey. Analysis of FIES data involves parameter estimation, statistical validation, and calculation of individual and population prevalence estimates, as appropriate, for food insecurity. In this analysis, a respondent’s raw score (an integer number between zero and eight) is determined. Based on this raw score, an interval measure of the severity of food security, based on global standards, is determined, by equating (calibrating the score on a common metric)</mark><sup>_33_</sup> <mark>. Equating is completed for each household, which allows us to estimate the probability of (i) moderate or severe and (ii) severe food insecurity among adult household members. Following procedures detailed by the Food and Agriculture Organization of the United Nations and the associated program, Voices of the Hungry, we calculate FIES for households in our data as follows:</mark> <mark>1. Beginning with Stata constructed data files, we construct binary variables for each of the eight FIES components that take a value of 1 for “Yes”, and 0 for “No” answers (and leave untouched any missing answers). We reorder the variables and recode the variable names to ensure the following order and naming convention: Worried, Healthy, FewFood, Skipped, AteLess, RunOut, Hungry, and WhlDay.</mark> <mark>2. We construct adult population weights (</mark> wa <mark>), by multiplying household sampling weights</mark> (wi,final <mark>) with the count of adult members in each household. This household sampling</mark> 16