COVID-19’s Impact on Low Income Countries

Abstract

The emergence of COVID-19 has profoundly affected social lives and economies globally, and unfortunately the vulnerable low-income population of the world has been adversely affected. On the whole, Covid19 has not only increased human causes, but containment measures have had a negative impact on societies, particularly low-income populations. Widespread adoption of containment measures such as lockdown has led to adverse effects such as mental health disorders, increased economic inequality, decreased employment opportunities, increased poverty trends, loss of income and spending, and other socio-economic consequences that have greatly damaged the lives of economically vulnerable households. . To analyze the effects of the pandemic on low-income households, The purpose of this research is to conduct a survey of the emerging literature on the effects of Covid19, examine the government's response, and recommend policies that will reduce harm to the low-income community. The increasing number of research studies published on the pandemic last year will give a deep insight into the misadventures and containment measures related to Covid19.

Gendered impact of COVID-19 on consumption of perishable and nonperishable food commodities in Pakistan

“…Moreover, lower educated households are also expected to be involved in laborious activities for livelihood with minimum chances of work from home during the pandemic affecting their income and food consumption. Low-income female- and male-headed households were more affected during COVID-19 compared to high-income people (Subohi, 2021). High-income female- and male-headed households are expected to have higher savings and financial capacity to sustain the income shocks due to COVID-19 in a better way, which may have helped them to lessen the repercussions of COVID-19 on their dietary patterns.…”

“…COVID-19 restrictions have disproportionate consequences in Pakistan for disadvantaged groups of society who work in informal sectors on a daily and contractual basis (Subohi, 2021). Several thousand informal workers lost their livelihood sources due to the pandemic in the country (Islam et al.…”

Examining structural and semantic predictors of announced sarcasm on r/AskReddit

“…For instance, quotation marks were coded as a yes/no binary variable because few comments had two or more pairs of quotation marks. Most of the features we extracted used dictionaries, adapted from several sources: negated and exaggerated words were retrieved from ChatGPT (OpenAI, 2023); Reddit slang was adapted from r/TheoryOfReddit glossary (i post gibberish, 2016); internet slang was retrieved from Penugonda (2021); emoticons (Sakib, 2021) from Kaggle; interjections from Holen's (n.d.) website; and a list of adverbs was included as a possible set of predictors after a preliminary descriptive analysis (using term frequency-inverse document frequency) suggested these words were more common in sarcastic than non-sarcastic comments. We also observed frequent occurrences of the word "yeah" in sarcastic comments from this preliminary investigation; so, we included this as a predictor in our analyses to more formally assess its contribution as a predictor of sarcasm.…”