Dataset Information

The socio-economic impacts of Covid-19 restrictions: Data from the coastal city of Mombasa, Kenya.

ABSTRACT: The novel corona virus disease (Covid-19) outbreak has caused great uncertainty in all spheres of human life. The experience has been incredibly humbling given that no country or section of society, regardless of its wealth or status, has been spared. The pandemic is not only a health crisis, but is also having serious damaging effects on societies, economies and vulnerable groups. Timely response is necessary in order to alleviate human suffering and to prevent irreversible destruction of livelihoods. This paper provides preliminary data on the socio-economic impacts of Covid-19 in the coastal city of Mombasa, Kenya, at the time of government-imposed curfews and cessation of movement. We conducted online surveys for two weeks during the restrictions period. The data was collected using online questionnaires directed at the city residents. The data highlights the mobile gender gap resulting from gender inequalities, residents' reliance on the government for Covid-19 information but lack of trust for government interventions, inadequate provisions of essential services, and the residents' lack of preparedness to tackle similar challenges in the future.

SUBMITTER: Kithiia J

PROVIDER: S-EPMC7499072 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The socio-economic impacts of Covid-19 restrictions: Data from the coastal city of Mombasa, Kenya.

Kithiia Justus J Wanyonyi Innocent I Maina Joseph J Jefwa Titus T Gamoyo Majambo M

Data in brief 20200918

The novel corona virus disease (Covid-19) outbreak has caused great uncertainty in all spheres of human life. The experience has been incredibly humbling given that no country or section of society, regardless of its wealth or status, has been spared. The pandemic is not only a health crisis, but is also having serious damaging effects on societies, economies and vulnerable groups. Timely response is necessary in order to alleviate human suffering and to prevent irreversible destruction of livel ...[more]

PMID: 32964076

Similar Datasets

Project description:BackgroundBrucellosis in Africa is caused by Brucella species transmitted through contaminated or contacts with infected animals or their carcasses. The disease reduces livestock production and reproduction performance evident by frequent episodes of abortion, still births, swollen testes, weak calves/lambs and swollen joints. However, the socio-economic impacts of these brucellosis-associated symptoms on milk, fat, meat and blood production, infertility, sale value, dowry and costs of treatment has not been evaluated extensively in developing countries. In Baringo County, Kenya, there is a continuous movement of cattle as a result of trade and grazing, which predisposes many herds to brucellosis infection. The objective of this study was to investigate the socio-economic impacts of Brucella infection on production systems for sheep, goats, cattle and camels and explore the impact of brucellosis on livestock production and reproduction performance among livestock keeping communities in Baringo County, Kenya. The study adopted a cross-sectional survey using quantitative data collection methods.ResultsResults demonstrated an impact on milk production in suspected brucellosis cases resulting from abortions (OR = 0.151, P < 0.0001) and swollen joints (OR = 2.881, P < 0.0001). In terms of infertility, abortion as a symptom of brucellosis (OR = 0.440, P = 0.002), still birth (OR = 0.628, P = 0.042), and weak calf or lamb (OR = 0.525, P = 0.005) had an impact on infertility. In terms of sale value, abortion (OR = 0.385, P = 0.008), weak calf/lamb (OR = 2.963, P = 0.013) had an impact on sale value. Other analyses demonstrated that for dowry, swollen testes (OR = 5.351, P = 0.032), weak calf and lambs (OR = 0.364, P = 0.019) had a likelihood of reduction of dowry value. Finally, in terms of cost of treatment, abortion (OR = 0.449, P = 0.001), still births (OR = 0.208, P = 0.015), swollen testes (OR = 0.78, P = 0.014), weak calf/lambs (OR = 0.178, P = 0.007) and swollen joints (OR = 0.217, P = 0.003) significantly increased the costs of treatments. There was no impact on fat and meat and blood production.ConclusionEven though there was a huge socio-economic impact on milk production, infertility, sale value, and dowry, it was the costs of treatment that was significantly impacted on all symptoms associated with brucellosis on this community. A 'One Health' approach in tackling the brucellosis menace as a holistic approach is recommended for both humans and their livestock.

Project description:BackgroundSocioeconomic determinants have been shown to have an effect on the progression of HIV disease evidenced by studies carried out largely in developed countries. Knowledge of these factors could inform on prioritization of populations during scale up of highly active antiretroviral therapy (HAART) constrained health systems. The objective of this study was to identify socioeconomic correlates of HIV disease progression in an adult Kenyan population.MethodsWe analysed data from 312 HIV positive individuals, drawn from a cohort enrolled in a randomized clinical trial investigating the effectiveness of Acyclovir in the prevention of HIV transmission among serodiscordant couples. In this study we included individuals with CD4 counts ≥ 350 cells/mm(3) and World Health Organization (WHO), clinical stage one or two. The exposure variables measured were: - daily household income available for expenditure, age, gender, housing type and level of formal education. We used a composite outcome of disease progression to WHO clinical stage 3 or 4 or a laboratory outcome of CD4 count below 350 cells/mm(3) after two years of follow-up. Logistic regression was used to determine associations of variables that were found to be significant at univariate analysis, and to control for potential confounders.ResultsSeventy eight (25 %) individuals reported HIV disease progression. Majority (79.9 %) were female. The median age was 30 year and 93.6 % had attained a primary level of education. Median CD4 at enrolment into the clinical trial was 564 cells/mm(3); those who had disease progression were enrolled with a significantly (p < 0.001) lower CD4 count. Daily household income available for expenditure adjusted for CD4 count at enrolment was associated significantly (p = 0.04) with HIV disease progression. Disease progression was five times more likely to occur in study subjects with daily income available for expenditure of less than US$1 compared to those with more than US$ 5 available for daily expenditure [adjusted Odds Ratio 4.6 (95 % Confidence Interval 1.4-14.4)]. Disease progression was not associated with age, gender, type of housing or level of education attained (p < 0.05).ConclusionPopulations with low household incomes should be considered vulnerable to disease progression and should therefore be prioritized during the scale up of HAART for treatment as prevention.

Project description:BackgroundCOVID-19 caused a worldwide outbreak leading the majority of human activities to a rough breakdown. Many stakeholders proposed multiple interventions to slow down the disease and number of papers were devoted to the understanding the pandemic, but to a less extend some were oriented socio-economic analysis. In this paper, a socio-economic analysis is proposed to investigate the early-age effect of socio-economic factors on COVID-19 spread.MethodsFifty-two countries were selected for this study. A cascade algorithm was developed to extract the R0 number and the day J*; these latter should decrease as the pandemic flattens. Subsequently, R0 and J* were modeled according to socio-economic factors using multilinear stepwise-regression.ResultsThe findings demonstrated that low values of days before lockdown should flatten the pandemic by reducing J*. Hopefully, DBLD is only parameter to be tuned in the short-term; the other socio-economic parameters cannot easily be handled as they are annually updated. Furthermore, it was highlighted that the elderly is also a major influencing factor especially because it is involved in the interactions terms in R0 model. Simulations proved that the health care system could improve the pandemic damping for low elderly. In contrast, above a given elderly, the reproduction number R0 cannot be reduced even for developed countries (showing high HCI values), meaning that the disease's severity cannot be smoothed regardless the performance of the corresponding health care system; non-pharmaceutical interventions are then expected to be more efficient than corrective measures.DiscussionThe relationship between the socio-economic factors and the pandemic parameters R0 and J* exhibits complex relations compared to the models that are proposed in the literature. The quadratic regression model proposed here has discriminated the most influencing parameters within the following approximated order, DLBL, HCI, Elderly, Tav, CO2, and WC as first order, interaction, and second order terms.ConclusionsThis modeling allowed the emergence of interaction terms that don't appear in similar studies; this led to emphasize more complex relationship between the infection spread and the socio-economic factors. Future works will focus on enriching the datasets and the optimization of the controlled parameters to short-term slowdown of similar pandemics.

Dataset Information

The socio-economic impacts of Covid-19 restrictions: Data from the coastal city of Mombasa, Kenya.

Publications

The socio-economic impacts of Covid-19 restrictions: Data from the coastal city of Mombasa, Kenya.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets