Public Health — Seattle & King County is monitoring changes in key economic, social, and other health indicators resulting from strategies to slow the spread of COVID-19.

What's in the Data?

This dataset tracks food insecurity across different demographics starting 4/23/2020 to 8/23/2021. It contains fields such as Race, Education, Sex, State, Income, etc. If you're looking for a dataset to examine Covid-19's impact on food insecurity for different demographics, then here you are!

Data Source

This data is from the United States Census Bureau's Pulse Survey. The Pulse Survey is a frequently updating survey designed to collect data on how people's lives have been impacted by the coronavirus. Specifically, this dataset is a cleaned up version of the ' Food Sufficiency for Households, in the Last 7 Days, by Select Characteristics" tables.

The original form of this data can be found at: https://www.census.gov/programs-surveys/household-pulse-survey/data.html

What was done to this data?

The original form of this data was split into 36 excel files containing ~67 sheets each. The data was in a non-tidy format, and questions were also not entirely standard. This dataset is my attempt to combine all these different files, tidy the data up, and combine slightly different questions together.

Why are there so many NA's?

The large amount of NA's are a consequence of how awful the data was originally/ forcing the data into a tidy format. Just filter the NA's out for the question you want to analyze and you'll be fine.

Abstract

Assessment of the impact of the COVID-19 pandemic on food security, livelihoods and local markets for refugees in urban areas.

Geographic coverage

Urban areas in Zimbabwe

Analysis unit

Household

Universe

Urban refugees

Kind of data

Sample survey data [ssd]

Sampling procedure

Random sampling

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The survey questionnaire comprises following modules: A- Demographics, B- Demographics, C- Food security, D- Markets, and E- Comments/ suggestion/ recommendations

As of February 2021, out of 1,238 people surveyed in Morocco, ** percent reported that having less income was a reason they had no access to food in the face of the coronavirus (COVID-19) pandemic. Lower-class households were the most affected in terms of lost sources of income in 2020. Furthermore, other barriers to food access indicated by the respondents included higher food prices, closure of food markets, and mobility-related restrictions, at **, **, and ** percent, respectively.

The COVID-19 pandemic is a “perfect storm” that is testing the resilience and functional stability of the food system, as it ultimately affects household food dynamics and consumer food experiences. This cross-national survey-based study examined in real time how the COVID-19 pandemic impacted food-centric matters in 1,732 Chinese and 1,547 U.S. households during the stay-at-home directives. Both cohorts reported increased efficiency in the use of food, families spending more time cooking and eating together, and more prudent use of food with less waste. Food purchasing patterns shifted from frequent trips to the store to dramatic increases in online ordering. A small proportion (2% U.S. and 11% Chinese respondents) reported clinically significant weight gains of >4.5 kg. Household food security weakened, with large increases in people worrying about or experiencing food shortage. Collective grocery-shopping experiences by survey respondents indicated that the functional stability of food supply systems remained steady; all food types were somewhat available, except for noticeably higher prices widely reported by the Chinese cohort. This study offers insights into food system resilience when facing the pandemic and sheds light on future food patterns as well as long-term questions for additional research about how people make decisions and food behavioral changes at times of crisis.

Multivariable logistic regression: Factors associated with adherence to COVID-19 mitigation recommendations and food security.

ABSTRACT: Objective: To estimate the prevalence of food insecurity among beneficiary and non-beneficiary university students of financial aid and associated factors. Methods: A cross-sectional study, with a probabilistic sample of 100 university students, was conducted at a federal university located on the coastal city of São Paulo in southeastern Brazil. The data made it possible to address sociodemographic aspects, food security and food quality markers. Data analysis involved descriptive statistics, Fisher’s exact association test and Mann-Whitney comparisons of means were used to investigate the prevalence of food insecurity between groups and associations with covariables at 5%. Results: The results revealed significant differences between groups. Receiving financial aid was associated with more vulnerability to facing food insecurity: 94% have some level of food insecurity (p=0.001); non-white skin color (p=0.019); overseeing one’s own income (p=0.001); the amount of money available to stay at the university (p=0.030). According to food quality markers, both groups often consumed ultra-processed foods (unhealthy quality marker). In contrast, most (92.3%) were concerned with consuming healthy foods. Conclusion: The pre-Covid-19 scenario reveals that despite receiving financial aid, a large part of students faced food insecurity in the three months prior to the study. Therefore, food insecurity should be recognized as a public health concern among university students, and adequate resources should be made available to avoid the occurrence of dropouts and assist in breaking the intergenerational cycle of social exclusion and the human right to food.

Abstract This article aims to analyze the intervention strategies adopted by public management during the COVID-19 pandemic to reduce food insecurity, based on a case study in the Brazilian state of Rio Grande do Norte. The study used a qualitative approach based on Program Theory and the multiple streams model to analyze the actions. In the state, the pandemic brought a window of opportunity, showing the importance of public policy in the government agenda, such as the program “Restaurante Popular,” which offers low-cost meals, and favors quick response and adequacy of means of implementation. The study highlights best practices, inspiring actions all over the country.

Univariate associations with participant food security.

An updated version of the food access and security during COVID-19 survey, based on experience with V2 nationally and throughout the US. Deployed in second national survey in Summer 2021. We are interested in collaborating with any individuals seeking to replication all or portions of the survey elsewhere.

The COVID-19 health crisis has brought on an economic crisis, and is rapidly exacerbating an ongoing food security and nutrition crisis. In a matter of weeks, COVID-19 has laid bare the underlying risks, fragilities, and inequities in global food systems, and pushed them close to breaking point.Our food systems have been sitting on a knife-edge for decades: children have been one school meal away from hunger; countries €“ one export ban away from food shortages; farms €“ one travel ban away from critical labour shortages; and families in the world’s poorest regions have been one missed day-wage away from food insecurity, untenable living costs, and forced migration

The coronavirus disease (COVID-19) pandemic has heightened food security risks in Asia and the Pacific. Disruptions to domestic and international food supply chains—caused as rising health risks led to major travel restrictions—have undermined food availability and accessibility. Domestically, disruptions in the upstream food supply chains have arisen from mobility restrictions and worker illnesses during planting and harvesting, in addition to hindered operations in processing, trucking, logistics, and trading. Losses of employment and income are also reducing food consumption, leaving vulnerable groups at risk of hunger and malnutrition. Basic food handouts are often limited and may not meet the nutritional needs of children and pregnant women. Internationally, border closures and export restrictions could imply limited availability and affordability of certain food items for countries that rely on imports.

BackgroundHousehold food insecurity (HFI) increased in Latin America by 9% between 2019 and 2020. Scant evidence shows who was unable to recover from the COVID-19 pandemic. Our aim was to use a Machine Learning (ML) approach to identify consistent and influential predictors of persistent moderate or severe HFI over 2 years.MethodsWe use a three-wave longitudinal telephone survey with a probabilistic sample representative of the Mexican population. With a response rate of 51.3 and 60.8% for the second and third waves, the final sample size consisted of 1,074 individuals. The primary outcome was persistent HFI, i.e., respondents who reported moderate or severe HFI in 2021 and 2022. Twelve income-related predictors were measured in 2020, including baseline HFI. We employed 6 supervised ML algorithms to cross-validate findings in models, examined its precision with 4 standard performance indicators to assess precision, and used SHAP values (Shapley Additive exPlanations) to identify influential predictors in each model.ResultsPrevalence of persistent moderate/severe HFI in 2021 and 2022 was 8.8%. Models with only a HFI 2020 baseline measure were used as a reference for comparisons; they had an accuracy of 0.79, a Cohen’s Kappa of 0.57, a sensitivity of 0.68, and a specificity of 0.88. When HFI was substituted by the suite of socioeconomic indicators, accuracy ranged from 0.70 to 0.84, Cohen’s Kappa from 0.40 to 0.67, sensitivity from 0.86 to 0.90, and specificity from 0.75 to 0.82. The best performing models included baseline HFI and socioeconomic indicators; they had an accuracy between 0.81 and 0.92, a Cohen’s Kappa between 0.61 and 0.85, a sensitivity from 0.74 to 0.95, and a specificity from 0.85 to 0.92. Influential and consistent predictors across the algorithms were baseline HFI, socioeconomic status (SES), adoption of financial coping strategies, and receiving government support.DiscussionPersistent HFI can be a relevant indicator to identify households that are less responsive to food security policies. These households should be prioritized for innovative government support and monitored to assess changes. Forecasting systems of HFI can be improved with longitudinal designs including baseline measures of HFI and socioeconomic predictors.

IntroductionSmall Island Developing States have disproportionately high food insecurity rates, related to complex challenges and vulnerabilities. The COVID-19 pandemic highlighted that within these settings, crises often overlap. We aimed to assess the impact of the concurrent COVID-19 pandemic and volcanic eruption on food production and security in St. Vincent and the Grenadines (SVG).MethodsAn interpretive mixed-methods study was conducted among a convenience sample of consenting adults ≥18 years from 100 households in SVG through a cross-sectional survey and participant interviews (10 households) between September 2021 and March 2022. Food insecurity prevalence over the past year was assessed using the Food Insecurity Experience Scale (FIES; Rasch modeling) and impacts to livelihoods from the pandemic and volcanic eruption was assessed using an adapted Caribbean COVID-19 Food Security and Livelihoods Impact Survey (Caribbean COVID-19 FS&L Survey). Data were analyzed using logistic regression.ResultsDuring the pandemic, 59% of the participants reported decreased income, 63% had no access to markets, 81% had no access to food aid; 34% of the participants had a change in food sources, and 81% reported that food production was negatively impacted by the volcanic eruptions, of which 68% reported decreased food production. The interviews highlighted that access to markets were restricted by fear of leaving home and contracting the COVID-19 virus, and participants who received food aid stated that the number of items were not sufficient for larger families. Almost half of the participants were severely food insecure [48% (95% C.I. 31.2,57.8)]; almost two thirds were moderately to severely food insecure [64% (95% C.I. 50.0, 74.2)]; mean FIES score 5.31 (95% C.I. 5.0,5.6). After adjusting for gender, age, education, and household size, moderate to severe food insecurity was associated with no access to food aid during the pandemic and post-eruptions (odds ratio 3.7; 95% confidence interval 1.5, 9.1; p = 0.004).ConclusionFood insecurity rates were high during the COVID-19 pandemic, exacerbated by volcanic eruptions and insufficient access to food aid. Our results suggest the need for the development of strategies and interventions aimed at increasing the resilience of food systems to mitigate the effects of future disasters.

🇺🇸 미국

The review is a component of the IDRC project with its primary objective to examine the existing evidence from the literature on the level of past and current vulnerability of the West African food system and the four pillars of food security. Food security of all countries can be considered vulnerable during times of crisis and pandemics. However, developing countries, such as those in West Africa, already struggle to meet the United Nations zero hunger goals prior to the onset of COVID-19. Many of these same countries had previously faced similar challenges during the recent Ebola virus outbreak, making it imperative for us to understand just how pandemics/epidemics affected, and continue affecting food security. The review will search for and include quantitative and qualitative research as well as opinion pieces and readily available grey literature (e.g. media reports). The review methodology follows PRISMA guidelines with the formal proposed protocol registered at doi.org/10.17605/OSF.IO/PKH98. A copy of the registered protocol is provided here.

Domestic Food Prices After COVID-19

Analyzing Impact on Developing Countries' Food Security

By [source]

About this dataset

This dataset looks at the effect of the COVID-19 pandemic on food prices in both domestic and international markets, particularly in developing countries. It contains data on monthly changes in food prices, categorised by country, market, price type (domestic or international) and commodities. In particular, this dataset provides insight into how the pandemic has impacted food security for those living in poorer countries where price increases may be more acutely felt. This dataset gives us a greater understanding of these changing dynamics of global food systems to enable more efficient interventions and support for those who are most vulnerable

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How to use the dataset

This dataset is an excellent resource for anyone looking to analyze the impact of COVID-19 on domestic food prices in developing countries. With this dataset, you can get an up-to-date overview of changes in the costs of various commodities in a given market and by a given price type. Additionally, you can filter data by commodity, country and price type.

In order to use this dataset effectively, here are some steps: - Identify your research question(s) - Filter the dataset by selecting specific columns that best answer your research question (ex: month, country, commodity) - Analyze the data accordingly (for example: Sorting the results then calculating averages). - Interpret results into actionable insights or visualizations

Research Ideas

• Analyzing trends in the cost of food items across different countries to understand regional disparities in food insecurity.
• Comparing pre- and post-COVID international food prices to study how nations altered their trade policies in response to the pandemic, indicating a shift towards or away from trading with other nations for food procurement.
• Using sentiment analysis to study consumer sentiment towards purchasing certain items based on their market prices, allowing businesses and governments alike to better target interventions aimed at improving access and availability of food supplies

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: dom_clean_data.csv | Column name | Description | |:---------------|:---------------------------------------------------------------------------| | month | The month in which the data was collected. (Date) | | country | The country in which the data was collected. (String) | | price_type | The type of price (domestic or international) that was collected. (String) | | market | The market in which the data was collected. (String) | | commodity | The type of commodity that was collected. (String) |

File: int_clean_data.csv | Column name | Description | |:---------------|:---------------------------------------------------------------------------| | country | The country in which the data was collected. (String) | | commodity | The type of commodity that was collected. (String) | | price_type | The type of price (domestic or international) that was collected. (String) | | time | The month in which the data was collected. (String) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit .

Supplementary information files for article Diet and food insecurity among mothers, infants and young children in Peru before and during COVID-19: a panel survey The COVID-19 pandemic may impact diet and nutrition through increased household food insecurity, lack of access to health services, and poorer quality diets. The primary aim of this study is to assess the impact of the pandemic on dietary outcomes of mothers and their infants and young children (IYC) in low-income urban areas of Peru. We conducted a panel study, with one survey prepandemic (n = 244) and one survey 9 months after the onset of COVID-19 (n = 254). We assessed breastfeeding and complementary feeding indicators and maternal dietary diversity in both surveys. During COVID-19, we assessed household food insecurity experience and economic impacts of the pandemic on livelihoods; receipt of financial or food assistance, and uptake of health services. Almost all respondents (98.0%) reported adverse economic impacts due to the pandemic and 46.9% of households were at risk of moderate or severe household food insecurity. The proportion of households receiving government food assistance nearly doubled between the two surveys (36.5%–59.5%). Dietary indicators, however, did not worsen in mothers or IYC. Positive changes included an increase in exclusive breastfeeding <6 months (24.2%–39.0%, p < 0.008) and a decrease in sweet food consumption by IYC (33.1%–18.1%, p = 0.001) and mothers (34.0%–14.6%, p < 0.001). The prevalence of sugar-sweetened beverage consumption remained high in both mothers (97%) and IYC (78%). In sum, we found dietary indicators had not significantly worsened 9 months into the COVID-19 pandemic. However, several indicators remain suboptimal and should be targeted in future interventions.

The novel coronavirus disease 2019 (COVID-19) is impacting families on an unprecedented scale across the state of Indiana. According to the US Bureau of Labor Statistics, the state's unemployment rate for May climbed to 16.9 percent, which is the highest number ever recorded in Indiana. Lost or reduced wages have resulted in significant food insecurity, and several resources that residents normally would depend on have become unavailable during the COVID-19 pandemic. Food banks are being stretched to their limit. School closures have changed access to free and reduced-cost breakfasts and lunches for students. Food staples normally available at grocery stores have become scarce.In response to the quickly spreading outbreak, the state of Indiana turned to the Geographic Information Office (GIO), within the Indiana Office of Technology, to fast-track the new, mobile-friendly Food Assistance Availability Map._Communities around the world are taking strides in mitigating the threat that COVID-19 (coronavirus) poses. Geography and location analysis have a crucial role in better understanding this evolving pandemic.When you need help quickly, Esri can provide data, software, configurable applications, and technical support for your emergency GIS operations. Use GIS to rapidly access and visualize mission-critical information. Get the information you need quickly, in a way that’s easy to understand, to make better decisions during a crisis.Esri’s Disaster Response Program (DRP) assists with disasters worldwide as part of our corporate citizenship. We support response and relief efforts with GIS technology and expertise.More information...