The number of hospitals in Ghana was forecast to continuously increase between 2024 and 2029 by in total one hopsital (+0.27 percent). The number of hospitals is estimated to amount to 371 hospitals in 2029. Depicted is the number of hospitals in the country or region at hand. As the OECD states, the rules according to which an institution can be registered as a hospital vary across countries.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of hospitals in countries like Nigeria and Ivory Coast.

The average number of hospital beds available per 1,000 people in Ghana was forecast to continuously decrease between 2024 and 2029 by in total 0.01 beds (-1.54 percent). The number of available beds per 1,000 people is estimated to amount to 0.64 beds in 2029. Depicted is the number of hospital beds per capita in the country or region at hand. As defined by World Bank this includes inpatient beds in general, specialized, public and private hospitals as well as rehabilitation centers.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the average number of hospital beds available per 1,000 people in countries like Ivory Coast and Senegal.

The number of hospital beds in Ghana was forecast to continuously increase between 2024 and 2029 by in total three thousand beds (+9.58 percent). After the fifteenth consecutive increasing year, the number of hospital beds is estimated to reach 34.29 thousand beds and therefore a new peak in 2029. Notably, the number of hospital beds of was continuously increasing over the past years.Depicted is the estimated total number of hospital beds in the country or region at hand.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of hospital beds in countries like Nigeria and Ivory Coast.

The current healthcare spending in Ghana was forecast to continuously increase between 2024 and 2029 by in total 1.1 billion U.S. dollars (+33.4 percent). After the fifth consecutive increasing year, the spending is estimated to reach 4.2 billion U.S. dollars and therefore a new peak in 2029. According to Worldbank health spending includes expenditures with regards to healthcare services and goods. The spending refers to current spending of both governments and consumers.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current healthcare spending in countries like Senegal and Ivory Coast.

The number of physicians in Ghana was forecast to continuously increase between 2024 and 2029 by in total 2.1 thousand physicians (+26.92 percent). After the tenth consecutive increasing year, the number of physicians is estimated to reach 9.94 thousand physicians and therefore a new peak in 2029. Depicted here is the estimated number of physicians in the geographical unit at hand. Thereby physicians include medical specialists as well as general practitioners.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of physicians in countries like Ivory Coast and Nigeria.

As part of efforts to reach the elimination target by 2030, the WHO and CDC recommend that all healthcare workers (HCWs) adhere to the 3-dose hepatitis B vaccination schedule to protect themselves against the infection. This study assessed Hepatitis B vaccination coverage and associated factors among personnel working in health facilities in Kumasi, Ghana. A cross-sectional study involving 530 HCWs was conducted in four hospitals in Kumasi from September to November 2023. An investigator-administered questionnaire was employed in gathering participant demographics and other information related to vaccination coverage. IBM SPSS version 26.0 and GraphPad Prism 8.0 were used for analysing the data. Even though, the majority (70.6%) reported having taken at least one dose of the vaccine, only 43.6% were fully vaccinated (≥ 3 doses). More than a quarter (29.4%) had not taken any dose of the HBV vaccine. Close to a quarter (23.6%) had not screened or tested for HBV infection in their lifetime..., Study Design and Population A cross-sectional study was conducted in four hospitals in Kumasi from 5th September to 9th November 2023. These study sites included 4 different hospitals. Kumasi, the second largest city in Ghana, is situated between latitudes 6.35°N and 6.40°N and longitudes 1.3°W and 1.35°W. Covering an area of approximately 150 square kilometres, it resides within the rainforest region of West Africa. The city has a population of around 2 million inhabitants [1]. In the suburbs of Kumasi [2], reported the prevalence levels of HBsAg are 6.78% in Garrison, 9.02% in Aboabo, and 10.0% in Tafo. The overall prevalence of HBsAg seropositivity within the study population was calculated to be 8.68%. These findings indicate that local prevalence rates of HBsAg can vary significantly within different areas of Kumasi. A total of 530 participants were recruited using a purposive sampling technique from the four different health facilities. The sample size was calculated using the Rao..., , # Hepatitis B vaccination coverage and associated factors among personnel working in health facilities in Kumasi, Ghana

Hepatitis B vaccination coverage and associated factors among personnel working in health facilities in Kumasi, Ghana.

[Access this dataset on Dryad: https://doi.org/10.5061/dryad.tmpg4f56b]

Summary of Dataset

This dataset contains information on the hepatitis B vaccination coverage and the associated factors among healthcare workers in health facilities in Kumasi, Ghana. The dataset captures information indicating the uptake of the hepatitis B vaccine by study participants. The cadre of professions, number of vaccination shots taken, perception of the cost of screening and vaccination, and more were captured as well. The data were collected using an investigator-administered questionnaire in a language that the study participants could easily comprehend (English and Twi).

Usage notes

Microsoft Excel ...

Abstract

The Kintampo north and south districts (previously simply referred to as the Kintampo district) are two of the 19 districts currently in the Brong Ahafo Region of Ghana. The Kintampo HDSS area (constituting of Kintampo North Municipality and Kintampo south district), has a surface area of 7,162 square kilometers. It is bounded to the north by the Black Volta, west by the Wenchi and Tain districts, in the East by the Atebubu District and to the south by Techiman and south-east by the Nkoranza north and south districts respectively.

The main indigenous ethnic groups are of the Bono, and the Mo origin. There is however a large permanent immigrant population from the northern Regions of Ghana (Dagarbas, Dagombas and Konkombas) who are mostly farmers. A few Dangbes and Ewes who are mainly fishermen are settled along the banks of the Black Volta. Settlements are mainly concentrated along the main trunk road linking the district capitals (Kintampo/Jema) to northern Region. There are 24 public health facilities made up of 15 Community-based Health Planning and Services (CHPS) compounds, 7 health centre and 2 hospitals. The hospitals are located at the district capitals. In the private sector, there are 3 private clinics and 3 private maternity homes In April 2010, The Kintampo HDSS established a satellite HDSS (Ahafo Mining Area Health and Demographic Surveillance System, AMAHDSS) in Tano North and Asutifi Districts of the Newmont Ghana Gold mining concession area. It is to monitor population and health dynamics in a mining area. It is the first HDSS in a mining area.

Geographic coverage

The Kintampo north and south districts (previously simply referred to as the Kintampo district) are two of the 19 districts currently in the Brong Ahafo Region of Ghana. The Kintampo HDSS area (constituting of Kintampo North Municipality and Kintampo south district), has a surface area of 7,162 square kilometers. It is bounded to the north by the Black Volta, west by the Wenchi and Tain districts, in the East by the Atebubu District and to the south by Techiman and south-east by the Nkoranza north and south districts respectively.

Analysis unit

Individual

Universe

The survey covered all resident population

Kind of data

Event history data

Frequency of data collection

Round 1 to Round 12: 2 times a year Round 13 to Round 22: 3 times a year

Sampling procedure

This dataset is not based on a sample, but contains information from the complete demographic surveillance area.

Sampling deviation

Not Applicable

Mode of data collection

Proxy Respondent [proxy]

Response rate

Response rate is 99% on an average over the years in all rounds

Sampling error estimates

Not Applicable

Data appraisal

CentreId MetricTable QMetric Illegal Legal Total Metric RunDate GH021 MicroDataCleaned Starts 254483 2017-05-17 12:26
GH021 MicroDataCleaned Transitions 0 700506 700506 0 2017-05-17 12:26
GH021 MicroDataCleaned Ends 254483 2017-05-17 12:26
GH021 MicroDataCleaned SexValues 32 700474 700506 0 2017-05-17 12:27
GH021 MicroDataCleaned DoBValues 32 700474 700506 0 2017-05-17 12:27

The current health expenditure as a share of the GDP in Ghana was forecast to continuously increase between 2024 and 2029 by in total 0.1 percentage points. The share is estimated to amount to 4.29 percent in 2029. According to Worldbank health spending includes expenditures with regards to healthcare services and goods. It is depicted here in relation to the total gross domestic product (GDP) of the country or region at hand.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current health expenditure as a share of the GDP in countries like Senegal and Nigeria.

This is the dataset and R script accompanying the manuscript "Fever in focus: symptoms, diagnoses, and treatment of febrile children in Ghana, a longitudinal hospital study."

Abstract

Survey based Harmonized Indicators (SHIP) files are harmonized data files from household surveys that are conducted by countries in Africa. To ensure the quality and transparency of the data, it is critical to document the procedures of compiling consumption aggregation and other indicators so that the results can be duplicated with ease. This process enables consistency and continuity that make temporal and cross-country comparisons consistent and more reliable.

Four harmonized data files are prepared for each survey to generate a set of harmonized variables that have the same variable names. Invariably, in each survey, questions are asked in a slightly different way, which poses challenges on consistent definition of harmonized variables. The harmonized household survey data present the best available variables with harmonized definitions, but not identical variables. The four harmonized data files are

a) Individual level file (Labor force indicators in a separate file): This file has information on basic characteristics of individuals such as age and sex, literacy, education, health, anthropometry and child survival. b) Labor force file: This file has information on labor force including employment/unemployment, earnings, sectors of employment, etc. c) Household level file: This file has information on household expenditure, household head characteristics (age and sex, level of education, employment), housing amenities, assets, and access to infrastructure and services. d) Household Expenditure file: This file has consumption/expenditure aggregates by consumption groups according to Purpose (COICOP) of Household Consumption of the UN.

Geographic coverage

National

Analysis unit

• Individual level for datasets with suffix _I and _L
• Household level for datasets with suffix _H and _E

Universe

The survey covered all de jure household members (usual residents).

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame and Units As in all probability sample surveys, it is important that each sampling unit in the surveyed population has a known, non-zero probability of selection. To achieve this, there has to be an appropriate list, or sampling frame of the primary sampling units (PSUs).The universe defined for the GLSS 5 is the population living within private households in Ghana. The institutional population (such as schools, hospitals etc), which represents a very small percentage in the 2000 Population and Housing Census (PHC), is excluded from the frame for the GLSS 5.

The Ghana Statistical Service (GSS) maintains a complete list of census EAs, together with their respective population and number of households as well as maps, with well defined boundaries, of the EAs. . This information was used as the sampling frame for the GLSS 5. Specifically, the EAs were defined as the primary sampling units (PSUs), while the households within each EA constituted the secondary sampling units (SSUs).

Stratification In order to take advantage of possible gains in precision and reliability of the survey estimates from stratification, the EAs were first stratified into the ten administrative regions. Within each region, the EAs were further sub-divided according to their rural and urban areas of location. The EAs were also classified according to ecological zones and inclusion of Accra (GAMA) so that the survey results could be presented according to the three ecological zones, namely 1) Coastal, 2) Forest, and 3) Northern Savannah, and for Accra.

Sample size and allocation The number and allocation of sample EAs for the GLSS 5 depend on the type of estimates to be obtained from the survey and the corresponding precision required. It was decided to select a total sample of around 8000 households nationwide.

To ensure adequate numbers of complete interviews that will allow for reliable estimates at the various domains of interest, the GLSS 5 sample was designed to ensure that at least 400 households were selected from each region.

A two-stage stratified random sampling design was adopted. Initially, a total sample of 550 EAs was considered at the first stage of sampling, followed by a fixed take of 15 households per EA. The distribution of the selected EAs into the ten regions or strata was based on proportionate allocation using the population.

For example, the number of selected EAs allocated to the Western Region was obtained as: 1924577/18912079*550 = 56

Under this sampling scheme, it was observed that the 400 households minimum requirement per region could be achieved in all the regions but not the Upper West Region. The proportionate allocation formula assigned only 17 EAs out of the 550 EAs nationwide and selecting 15 households per EA would have yielded only 255 households for the region. In order to surmount this problem, two options were considered: retaining the 17 EAs in the Upper West Region and increasing the number of selected households per EA from 15 to about 25, or increasing the number of selected EAs in the region from 17 to 27 and retaining the second stage sample of 15 households per EA.

The second option was adopted in view of the fact that it was more likely to provide smaller sampling errors for the separate domains of analysis. Based on this, the number of EAs in Upper East and the Upper West were adjusted from 27 and 17 to 40 and 34 respectively, bringing the total number of EAs to 580 and the number of households to 8,700.

A complete household listing exercise was carried out between May and June 2005 in all the selected EAs to provide the sampling frame for the second stage selection of households. At the second stage of sampling, a fixed number of 15 households per EA was selected in all the regions. In addition, five households per EA were selected as replacement samples.The overall sample size therefore came to 8,700 households nationwide.

Mode of data collection

Face-to-face [f2f]

BackgroundRegular evaluation of caesarean section (CS) is required due to their rising trend and outcomes. Many women recently opt for elective CS, even in resource-constrained settings. Data evaluating the outcomes of CS is however sparse. Hence, this study sought to determine the rate of fetal mortalities and their determinants following CS in the Tatale District Hospital of the Northern Region, Ghana.MethodsA retrospective cross-sectional study was employed to analyze the medical records of 275 women who underwent CS from 2019 to 2021. Data were collected from the hospital’s record of CS cases from 2019 to 2021. Descriptive statistics were used to summarize the data and Pearson’s chi-square/Fisher’s exact test was used to examine the relationship between maternal and obstetric characteristics and fetal mortality. At a 95% confidence interval (95% CI), logistic regression was fitted to assess significant variables and reported the results using odds ratio.ResultsOf 1667 deliveries, 16.5% of the mothers gave birth by CS. A fetal mortality rate of 76.4 per 1000 total births was recorded following CS. Babies born with low Appearance, Pulse, Grimace, Activity and Respiration (APGAR) scores (0–3) at fifth-minute had an increased risk of fetal mortality (AOR  =  523.19, 95%CI: 49.24–5559.37, p  =  

The current healthcare spending per capita in Ghana was forecast to continuously increase between 2024 and 2029 by in total 20.5 U.S. dollars (+22.15 percent). After the fourth consecutive increasing year, the spending is estimated to reach 113.05 U.S. dollars and therefore a new peak in 2029. Depicted here is the average per capita spending, in a given country or region, with regards to healthcare. The spending refers to the average current spending of both governments and consumers per inhabitant.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current healthcare spending per capita in countries like Ivory Coast and Nigeria.

Cervical cancer screening has reduced cervical cancer-related mortality by over 70% in countries that have achieved high coverage. However, there are significant geographic disparities in access to screening. In Ghana, although cervical cancer is the second most common cancer in women, there is no national-level cervical cancer screening program, and only 2 to 4% of eligible Ghanaian women have ever been screened for cervical cancer. This study used an exploratory, sequential mixed-methods approach to examine barriers and facilitators to cervical cancer screening from women and healthcare workers perspectives, guided by the Dynamic Sustainability Framework. Two convenience samples of 215 women and 17 healthcare personnel were recruited for this study. All participants were from one of three selected clinics (Ejisu Government Hospital, Kumasi South Hospital, and the Suntreso Government Hospital) in the Ashanti region of Ghana. Descriptive analyses were used to group the data by practice setting and ecological system. Statistical differences in means and proportions were used to evaluate women’s barriers to cervical cancer screening. Quantitative findings from the women’s survey informed qualitative, in-depth interviews with the healthcare workers and analyzed using an inductive thematic analysis. The median age of women and healthcare workers was 37.0 years and 38.0 years respectively. Most women (n=194, 90.2%) reported never having been screened. Women who had not been screened were more likely to have no college or university education. Ecologic factors identified were lack of knowledge about available services, distance to a clinic and requiring a spouse’s permission prior to scheduling. Practice setting barriers included long clinic wait times and culturally sensitive issue. The quantitative and qualitative data were integrated in the data collection stage, results, and subsequent discussion. These findings highlight the need for non-clinician-based culturally sensitive tool options for screening such as self-collected HPV tests to increase screening participation in Ghana.

This feature layer provides access to OpenStreetMap (OSM) point data of medical facilities for Africa, which is updated every 15 minutes with the latest edits. This hosted feature layer view is referencing a hosted feature layer of OSM point (node) data in ArcGIS Online that is updated with minutely diffs from the OSM planet file. This feature layer view includes amenity features defined as a query against the hosted feature layer where the amenity value is any of 'hospital', 'clinic', 'doctors', or 'pharmacy'.In OSM, amenities are useful and important facilities for visitors and residents, such as hospitals and clinics. These features are identified with an amenity tag. There are thousands of different tag values used in the OSM database. In this feature layer, unique symbols are used for the most common amenity tags used for medical facilities.Zoom in to large scales (e.g. Neighborhood level or 1:20k scale) to see the amenity features display. You can click on a feature to get the name of the amenity. The name of the amenity will display by default at very large scales (e.g. Building level of 1:2k scale). Labels can be turned off in your map if you prefer.Create New LayerIf you would like to create a more focused version of this medical facilities layer displaying just one or two amenity types, you can do that easily! Just add the layer to a map, copy the layer in the content window, add a filter to the new layer (e.g. amenity is hospital), rename the layer as appropriate, and save layer. You can also change the layer symbols or popup if you like. Esri will publish a few such layers (e.g. Places of Worship, Schools, and Parking) that are ready to use, but not for every type of amenity.Important Note: if you do create a new layer, it should be provided under the same Terms of Use and include the same Credits as this layer. You can copy and paste the Terms of Use and Credits info below in the new Item page as needed.

This statistic shows a ranking of the estimated current healthcare spending per capita in 2020 in Africa, differentiated by country. The spending refers to the average current spending of both governments and consumers per inhabitant.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

BackgroundIn Ghana, temperature check at various points of entry was adopted as a means of screening people for coronavirus disease 2019 without taking into consideration data on the local prevalence of fever associated with the disease. Our objective was to assess fever prevalence and its associated risk factors among patients hospitalised with coronavirus disease 2019 at the Eastern Regional Hospital, Koforidua in Ghana.MethodsWe reviewed medical records of 301 coronavirus disease 2019 patients who were admitted at the Eastern Regional Hospital, Koforidua between May 5, 2020, and August 31, 2021. Data collected on a pre-designed extraction sheet was processed, entered and analysed using Microsoft excel 2019 and Stata/IC version 16.1 software. Prevalence of fever was estimated and a multivariable logistic regression model was fitted to establish risk factors associated with fever among hospitalised coronavirus disease 2019 patients. A relationship was accepted to be significant at 5% level of significance.ResultsThe prevalence of fever among hospitalised coronavirus disease 2019 patients was 21.6% (95% CI, 17.1%-26.7%). Risk factors associated with fever were age group [0–19 years (AOR, 5.75; 95% CI, 1.46–22.68; p = 0.013); 20–39 years (AOR, 3.22; 95% CI, 1.42–7.29; p = 0.005)], comorbidity (AOR, 2.18; 95% CI, 1.04–4.59; p = 0.040), and disease severity [moderate (AOR, 3.89; 95% CI, 1.44–10.49; p = 0.007); severe (AOR, 4.08; 95% CI, 1.36–12.21; p = 0.012); critical (AOR, 4.85; 95% CI, 1.03–22.85; p = 0.046)].ConclusionsThe prevalence of fever was low among hospitalised coronavirus disease 2019 patients at the Eastern Regional Hospital, Koforidua. However, there was an increasing risk of fever as the disease severity progresses. Fever screening may be utilised better in disease of higher severity; it should not be used alone especially in mild disease.

Characteristics of mothers who participated in the study (n = 72).

Characteristics of healthcare providers who participated in the study (n = 43).

Encephalitis is an inflammation of the functional tissues of the brain and is characterised by an acute onset of fever, altered mental status and the onset of seizures. Viruses constitute the major aetiology for encephalitis and molecular diagnostic techniques such as Polymerase Chain Reaction (PCR) and genome sequencing are the preferred diagnostic techniques for confirmation of viral aetiology. In this study, we determined the viruses associated with encephalitis among patients presenting to a major referral hospital in Ghana. We also assessed the clinical epidemiology, risk factors/determinants and outcome of individuals who presented with signs and symptoms of encephalitis in a tertiary hospital setting in Ghana.

Awareness of MDs among physicians.