scholarly journals Citizens lack access to healthcare facilities: How COVID‐19 lockdown and social distancing policies boost roadside chemist businesses in South‐Eastern Nigeria

2021 ◽  
Author(s):  
Victor Chidubem Iwuoha ◽  
Ernest Toochi Aniche ◽  
Charles Arinze Obiora ◽  
Uchenna T. Umeifekwem
Keyword(s):  
Access To Healthcare ◽  
Healthcare Facilities ◽  
Social Distancing ◽  
South Eastern

scholarly journals Mapping physical access to healthcare for older adults in sub-Saharan Africa: A cross-sectional analysis with implications for the COVID-19 response

2020 ◽  
Author(s):  
Pascal Geldsetzer ◽  
Marcel Reinmuth ◽  
Paul O Ouma ◽  
Sven Lautenbach ◽  
Emelda A Okiro ◽  
...  
Keyword(s):  
Older Adults ◽  
Travel Time ◽  
Healthcare Facility ◽  
Access To Healthcare ◽  
Sub Saharan Africa ◽  
Travel Times ◽  
Healthcare Resources ◽  
Healthcare Facilities ◽  
Sub Saharan ◽  
Physical Access

Background: SARS-CoV-2, the virus causing coronavirus disease 2019 (COVID-19), is rapidly spreading across sub-Saharan Africa (SSA). Hospital-based care for COVID-19 is particularly often needed among older adults. However, a key barrier to accessing hospital care in SSA is travel time. To inform the geographic targeting of additional healthcare resources, this study aimed to determine the estimated travel time at a 1km x 1km resolution to the nearest hospital and to the nearest healthcare facility of any type for adults aged 60 years and older in SSA. Methods: We assembled a unique dataset on healthcare facilities' geolocation, separately for hospitals and any type of healthcare facility (including primary care facilities) and including both private- and public-sector facilities, using data from the OpenStreetMap project and the KEMRI Wellcome Trust Programme. Population data at a 1km x 1km resolution was obtained from WorldPop. We estimated travel time to the nearest healthcare facility for each 1km x 1km raster using a cost-distance algorithm. Findings: 9.6% (95% CI: 5.2% - 16.9%) of adults aged 60 and older years had an estimated travel time to the nearest hospital of longer than six hours, varying from 0.0% (95% CI: 0.0% - 3.7%) in Burundi and The Gambia, to 40.9% (95% CI: 31.8% - 50.7%) in Sudan. 11.2% (95% CI: 6.4% - 18.9%) of adults aged 60 years and older had an estimated travel time to the nearest healthcare facility of any type (whether primary or secondary/tertiary care) of longer than three hours, with a range of 0.1% (95% CI: 0.0% - 3.8%) in Burundi to 55.5% (95% CI: 52.8% - 64.9%) in Sudan. Most countries in SSA contained populated areas in which adults aged 60 years and older had a travel time to the nearest hospital of more than 12 hours and to the nearest healthcare facility of any type of more than six hours. The median travel time to the nearest hospital for the fifth of adults aged 60 and older years with the longest travel times was 348 minutes (IQR: 240 - 576 minutes) for the entire SSA population, ranging from 41 minutes (IQR: 34 - 54 minutes) in Burundi to 1,655 minutes (IQR: 1065 - 2440 minutes) in Gabon. Interpretation: Our high-resolution maps of estimated travel times to both hospitals and healthcare facilities of any type can be used by policymakers and non-governmental organizations to help target additional healthcare resources, such as new make-shift hospitals or transport programs to existing healthcare facilities, to older adults with the least physical access to care. In addition, this analysis shows precisely where population groups are located that are particularly likely to under-report COVID-19 symptoms because of low physical access to healthcare facilities. Beyond the COVID-19 response, this study can inform countries' efforts to improve care for conditions that are common among older adults, such as chronic non-communicable diseases.

scholarly journals Combined epidemiological and genomic analysis of nosocomial SARS-CoV-2 transmission identifies community social distancing as the dominant intervention reducing outbreaks

2020 ◽  
Author(s):  
Luke B Snell ◽  
Chloe L Fisher ◽  
Usman Taj ◽  
Blair Merrick ◽  
Adela Alcolea-Medina ◽  
...  
Keyword(s):  
Incubation Period ◽  
Sequence Data ◽  
Sequence Similarity ◽  
Genomic Analysis ◽  
Nosocomial Transmission ◽  
Robust Estimate ◽  
Healthcare Facilities ◽  
Social Distancing ◽  
High Prevalence ◽  
Preventative Interventions

ABSTRACTMany healthcare facilities report SARS-CoV-2 outbreaks but transmission analysis is complicated by the high prevalence of infection and limited viral genetic diversity. The contribution of different vectors to nosocomial infection or the effectiveness of interventions is therefore currently unclear. Detailed epidemiological and viral nanopore sequence data were analysed from 574 consecutive patients with a PCR positive SARS-CoV-2 test between March 13th and March 31st, when the pandemic first impacted on a large, multisite healthcare institution in London. During this time the first major preventative interventions were introduced, including progressive community social distancing (CSD) policies leading to mandatory national lockdown, exclusion of hospital visitors, and introduction of universal surgical facemask-use by healthcare-workers (HCW). Incidence of nosocomial cases, community SARS-CoV-2 cases and infection in a cohort of 228 HCWs followed the same dynamic course, decreasing shortly after introduction of CSD measures and prior to the main hospital-based interventions. We investigated clusters involving nosocomial cases based on overlapping ward-stays during the 14-day incubation period and SARS-CoV-2 genome sequence similarity. Our method placed 63 (79%) of 80 sequenced probable and definite nosocomial cases into 14 clusters containing a median of 4 patients (min 2, max 19) No genetic support was found for the majority of epidemiological clusters (31/44, 70%) and genomics revealed multiple contemporaneous outbreaks within single epidemiological clusters. We included a measure of hospital enrichment compared to community cases to increase confidence in our clusters, which were 1-14 fold enriched. Applying genomics, we could provide a robust estimate of the incubation period for nosocomial transmission, with a median lower bound and upper bound of 6 and 9 days respectively. Six (43%) clusters spanned multiple wards, with evidence of cryptic transmission, and community-onset cases could not be identified in more than half the clusters, particularly on the elective hospital site, implicating HCW as vectors of transmission. Taken together these findings suggest that CSD had the dominant impact on reducing nosocomial transmission by reducing HCW infection.

scholarly journals What We Do Not Know about COVID-19 and Social Distancing

2020 ◽  
Author(s):  
Samina Masood
Keyword(s):  
Growth Pattern ◽  
Probabilistic Approach ◽  
Ecological Condition ◽  
Economic Conditions ◽  
Similar Distribution ◽  
Saturation Point ◽  
Healthcare Facilities ◽  
Social Distancing ◽  
The Impact ◽  
Rna And Dna

We present the detailed calculations of social distancing requirement. A comparative study of the growth pattern and death tolls in different communities indicates that the growth pattern of infected patients and death rate follow the similar distribution with different parametrizations. Every distribution follows an exponential growth pattern curve, like other microbes, then reaches the saturation point an d eventually decay s However, the argument for the exponential function depends on several parameters unbeknownst, as of yet. However, the slope varies different ial ly for various epicenter s and seems to have a relationship with parameters such as accessibi lity to healthcare facilities, pre existing medical conditions socio economic conditions and lifestyle. The mismatch of the growth pattern is also linked with the impact of various other factors and a premature interpretation of limit ed data. Novel behavi or of the virus brought many surprises, opened up new venues for medical research, and the need for the more detailed study of pathogens in the light of the interaction of RNA and DNA The adaptability to diverse ecological condition s and the relevant modification in the structure is also worth investigation The genetic modification can be studied using quantum mechanical probabilistic approach.

Impact of COVID-19 lockdown and social distancing policies on small businesses in south-eastern Nigeria: whither the stimulus packages?

2021 ◽  
Author(s):  
Victor Chidubem Iwuoha ◽  
Ernest Toochi Aniche ◽  
Gerald Ekenedirichukwu Ezirim ◽  
Ikenna Mike Alumona ◽  
Josephine Nneka Obiorji
Keyword(s):  
Small Businesses ◽  
Survey Methods ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Social Distancing ◽  
South Eastern ◽  
Business Units ◽  
Policy Interventions ◽  
Income Stream ◽  
Negative Impacts

This article examines the specific or sub-sectoral effects of COVID-19 lockdown measures on small business units, thus departing from previous studies which only focused on general effects. Based on qualitative and cross-sectional survey methods, the article depicts a cross-sectoral disparity in the patronage level and income stream of customers of small businesses found on the streets of south-eastern Nigeria. The article identifies the gap in the policy interventions meant to cushion the negative impacts of COVID-19 lockdown and social distancing policies on small businesses. Hence, state policy interventions have not had the cushioning impact on small businesses in south-eastern Nigeria. A pro-poor approach towards the review of the policy interventions is highly imperative.

scholarly journals Determinants of Women Access to Healthcare Services in Sub-Saharan Africa

2019 ◽  
Vol 12 (1) ◽  
pp. 504-514 ◽  
Author(s):  
Azuh Dominic ◽  
Adeyemi Ogundipe ◽  
Oluwatomisin Ogundipe
Keyword(s):  
Health Service ◽  
Service Utilization ◽  
Health Service Utilization ◽  
Generalized Method Of Moments ◽  
Healthcare Services ◽  
Access To Healthcare ◽  
Sub Saharan Africa ◽  
Service Availability ◽  
Healthcare Facilities ◽  
Sub Saharan

Background: The study examined the socio-economic determinants of women access to healthcare services in Sub-Saharan Africa for the period 1995-2015. Methods: The study adopted the dynamic panel model and estimated it using the System Generalized Method of Moments in a bid to overcome the endogeneity problem inherent in the model of study. Result: The study harmonized the theoretical strands in the literature by describing the measure of access determinants as three main components; i. Health service availability, ii. Health service utilization and iii. Health service decision. Conclusion: The indicators of health service availability such as community health workers, physicians, nurses and midwives and hospital beds improve women's access to healthcare facilities in Africa. Also, health service utilization indicators such as population density worsen the quality of healthcare services available to women while electricity access and private health expenditure enhance women’s access to quality healthcare delivery. Health service decision indicators such as female bank account ownership, female labour force participation, attainment of basic education and female household headship were important in enhancing women's access to healthcare facilities. Generally, women's health outcomes were more responsive to health service utilization; implying that service utilization is an important proof of healthcare access in Africa.

scholarly journals Access to Public Healthcare Services in Urban Areas in Nigeria: The Influence of Demographic and Socioeconomic Characteristics of the Urban Population

2021 ◽  
pp. 1-13
Author(s):  
Abubakar Abdullahi ◽  
Nalika Gunawardena
Keyword(s):  
Urban Areas ◽  
Urban Population ◽  
Economic Status ◽  
Composite Index ◽  
Healthcare Services ◽  
Access To Healthcare ◽  
Public Healthcare ◽  
Chi Square ◽  
Significance Level ◽  
Healthcare Facilities

Background: Ensuring access to healthcare facilities is a high priority need in developing countries. This research aimed to determine the influence of socio-demographic and economic characteristics of the urban population in Nigeria to access to public healthcare facilities. Methods: We conducted a community-based study in 400 households across the three urban areas of Gombe state, Nigeria. Access to healthcare facilities was quantified in a composite index which considers availability, accessibility and affordability. The head of families was interviewed for information related to access and for the socio-demographic and economic status of the residences. The influence of socio-demographic and economic characteristics was determined using a chi-square test with a significance level of <0.05. Results: Most of the population interviewed within the selected urban areas had good access (84%) to public healthcare facilities. Socio-demographic and economic characteristics of household representatives such as age (p = 0.02), religious status (p = 0.00), level of education (p =0 .00), employment (p = 0.00) and possession of healthcare insurance (p = 0.00) were found to significantly influence access to healthcare facilities in urban areas. Conclusion:  Access to public healthcare facilities within the urban areas was good and the study revealed some modifiable socio-demographic and economic factors that influence access. We recommend the intervention to address the factors to further improve access to public healthcare facilities and to achieve universal healthcare coverage.

scholarly journals Impact of Traffic Congestion on Spatial Access to Healthcare Services in Nairobi: an ecological study

2021 ◽  
Author(s):  
Mutono Nyamai ◽  
Jim A. Wright ◽  
Mumbua Mutunga ◽  
Henry Mutembei ◽  
SM Thumbi
Keyword(s):  
Health Facility ◽  
Traffic Congestion ◽  
One Health ◽  
Healthcare Professionals ◽  
Access To Healthcare ◽  
Health Care Facilities ◽  
Health Facilities ◽  
Healthcare Facilities ◽  
African Cities ◽  
Geographical Access

Abstract Background Geographic accessibility is an important determinant of healthcare utilisation and is critical for achievement of universal health coverage. Despite the high disease burden and severe traffic congestion in many African cities, few studies have assessed how traffic congestion impacts geographical access to healthcare facilities and to health professionals in these settings. Methods Using data on health facilities obtained from the Ministry of Health in Kenya, we mapped 944 primary, 94 secondary and four tertiary healthcare facilities in Nairobi County. We then used traffic probe data to identify areas within a 15-, 30- and 45-minute drive from each health facility during peak and off-peak hours and calculated the proportion of the population with access to healthcare in the County. We employed a 2-step floating catchment area model to calculate the ratio of healthcare and healthcare professionals to population during these times. Results During peak hours, <70% of Nairobi’s 4.1 million population was within a 30-minute drive from a health facility. This increased to >75% during off-peak hours. In 45 minutes, the majority of the population had an accessibility index of one health facility accessible to more than 100 people (<0.01) for primary health care facilities while secondary and tertiary health facilities had a ratio of one health facility for more than 10,000 people (<0.0001) and at least two health facilities per 100,000 people (>0.00002) respectively. Of people with access to health facilities, a sub-optimal ratio of <2.3 healthcare professionals per 1000 people was observed in facilities offering primary and secondary healthcare during peak and off-peak hours. Conclusion These findings can guide urban planners and policymakers in improving access to healthcare facilities to optimise coverage during peak and off-peak traffic times. Similarly, growing availability of traffic probe data in African cities should enable similar analysis in other countries.

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