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 Travel-time, bikes, and HIV elimination in Malawi: a geospatial modeling analysis

2020 ◽  
Author(s):  
Laurence Palk ◽  
Justin T Okano ◽  
Luckson Dullie ◽  
Sally Blower
Keyword(s):  
Travel Time ◽  
Rural Areas ◽  
Hiv Treatment ◽  
Sub Saharan Africa ◽  
People Living With Hiv ◽  
Travel Times ◽  
Geospatial Modeling ◽  
Healthcare Facilities ◽  
Fast Tracking ◽  
Sub Saharan

Background: UNAIDS has prioritized Malawi and 21 other countries in sub-Saharan Africa (SSA) for "fast-tracking" the end of their HIV epidemics. To achieve elimination requires treating 90% of people living with HIV (PLHIV); coverage is already fairly high (70-75%). However, many individuals in SSA have to walk to access healthcare. We use data-based geospatial modeling to determine whether the need to travel long distances to access treatment and limited transportation in rural areas are barriers to HIV elimination in Malawi. Additionally, we evaluate the effect on treatment coverage of increasing the availability of bicycles in rural areas. Methods: We build a geospatial model that we use to estimate, for every PLHIV, their travel-time to access HIV treatment if driving, bicycling, or walking. We estimate the travel-times needed to achieve 70% or 90% coverage. Our model includes a spatial map of healthcare facilities (HCFs), the geographic coordinates of residencies for all PLHIV, and an "impedance" map. We quantify impedance using data on road/river networks, land cover, and topography. Findings: To cross an area of one km2 in Malawi takes from ~60 seconds (driving on main roads) to ~60 minutes (walking in mountainous areas); ~80% of PLHIV live in rural areas. At ~70% coverage, HCFs can be reached within: ~45 minutes if driving, ~65 minutes if bicycling, and ~85 minutes if walking. Increasing coverage above ~70% will become progressively more difficult. To achieve 90% coverage, the travel-time for many PLHIV (who have yet to initiate treatment) will be almost twice as long as those currently on treatment. Increasing bicycle availability in rural areas reduces round-trip travel-times by almost one hour (in comparison with walking), and could substantially increase coverage levels. Interpretation: Geographic inaccessibility to treatment coupled with limited transportation in rural areas are substantial barriers to reaching 90% coverage in Malawi. Increased bicycle availability could help eliminate HIV. Funding: National Institute of Allergy and Infectious Diseases

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 Exploring country-wide equitable government health care facility access in Uganda

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Nicholas Dowhaniuk
Keyword(s):  
Health Care ◽  
Random Forest ◽  
Health Center ◽  
Travel Time ◽  
Health Centers ◽  
Sub Saharan Africa ◽  
Walking Distance ◽  
Laboratory System ◽  
Government Health ◽  
Sub Saharan

Abstract Background Rural access to health care remains a challenge in Sub-Saharan Africa due to urban bias, social determinants of health, and transportation-related barriers. Health systems in Sub-Saharan Africa often lack equity, leaving disproportionately less health center access for the poorest residents with the highest health care needs. Lack of health care equity in Sub-Saharan Africa has become of increasing concern as countries enter a period of simultaneous high infectious and non-communicable disease burdens, the second of which requires a robust primary care network due to a long continuum of care. Bicycle ownership has been proposed and promoted as one tool to reduce travel-related barriers to health-services among the poor. Methods An accessibility analysis was conducted to identify the proportion of Ugandans within one-hour travel time to government health centers using walking, bicycling, and driving scenarios. Statistically significant clusters of high and low travel time to health centers were calculated using spatial statistics. Random Forest analysis was used to explore the relationship between poverty, population density, health center access in minutes, and time saved in travel to health centers using a bicycle instead of walking. Linear Mixed-Effects Models were then used to validate the performance of the random forest models. Results The percentage of Ugandans within a one-hour walking distance of the nearest health center II is 71.73%, increasing to 90.57% through bicycles. Bicycles increased one-hour access to the nearest health center III from 53.05 to 80.57%, increasing access to the tiered integrated national laboratory system by 27.52 percentage points. Significant clusters of low health center access were associated with areas of high poverty and urbanicity. A strong direct relationship between travel time to health center and poverty exists at all health center levels. Strong disparities between urban and rural populations exist, with rural poor residents facing disproportionately long travel time to health center compared to wealthier urban residents. Conclusions The results of this study highlight how the most vulnerable Ugandans, who are the least likely to afford transportation, experience the highest prohibitive travel distances to health centers. Bicycles appear to be a “pro-poor” tool to increase health access equity.

scholarly journals Electrocardiographic Reference Values for a Population of Older Adults in Sub-Saharan Africa

2013 ◽  
Vol 19 (1) ◽  
pp. 34-42 ◽  
Author(s):  
Matthew J. Dewhurst ◽  
Luigi Y. Di Marco ◽  
Felicity Dewhurst ◽  
Philip C. Adams ◽  
Alan Murray ◽  
...  
Keyword(s):  
Older Adults ◽  
Reference Values ◽  
Sub Saharan Africa ◽  
Sub Saharan

Challenges and Assets of Older Adults in Sub-Saharan Africa: Perspectives of Gerontology Scholars

2021 ◽  
pp. 1-19
Author(s):  
Margaret E. Adamek ◽  
Messay Gebremariam Kotecho ◽  
Samson Chane ◽  
Getachew Gebeyaw
Keyword(s):  
Older Adults ◽  
Sub Saharan Africa ◽  
Sub Saharan

scholarly journals Predictors of three-month mortality among hospitalized older adults in Togo

2020 ◽  
Author(s):  
Fifonsi Adjidossi GBEASOR-KOMLANVI ◽  
Martin Kouame TCHANKONI ◽  
Akila Wimima BAKOUBAYI ◽  
Matthieu Yaovi LOKOSSOU ◽  
Arnold SADIO ◽  
...  
Keyword(s):  
Older Adults ◽  
Hospital Mortality ◽  
Cox Regression ◽  
Sub Saharan Africa ◽  
Mortality Data ◽  
Kaplan Meier ◽  
All Cause Mortality ◽  
Hospitalized Older Adults ◽  
Sub Saharan

Abstract Background: Assessing hospital mortality and its predictors is important as some of these can be prevented through appropriate interventions. Few studies have reported hospital mortality data among older adults in sub-Saharan Africa. The objective of this study was to assess the mortality and associated factors among hospitalized older adults in Togo.Methods: We conducted a prospective cohort study from February 2018 to September 2019 among patients ≥50 years admitted in medical and surgical services of six hospitals in Togo. Data were recorded during hospitalization and through telephone follow-up survey within 90 days after admission. The main outcome was all-cause mortality at 3 months. Survival curves were estimated using the Kaplan-Meier method and Cox regression analyses were performed to assess predictors of mortality.Results: The median age of the 650 older adults included in the study period was 61 years, IQR: [55-70] and at least one comorbidity was identified in 59.7% of them. The all-cause mortality rate of 17.2% (95%CI: 14.4-20.4) and the majority of death (93.7%) occurred in hospital. Overall survival rate was 85.5% and 82.8% after 30 and 90 days of follow-up, respectively. Factors associated with 3-month mortality were the hospital level in the health pyramid, hospitalization service, length of stay, functional impairment, depression and malignant diseases.Conclusion: Togolese health system needs to adjust its response to an aging population in order to provide the most effective care.

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