The effect of distance to health-care facilities on childhood mortality in rural Burkina Faso

Mapping Access to Children's Hospitals in Texas

Vehicle access, travel time, and distance to hospitals and emergency rooms with sufficient patient beds are critical healthcare accessibility measures, especially for children who require specific pediatric services. In a large state like Texas with vast rural areas and limited public transit infrastructure, 75% of the children live over an hour from the closest facility that provides pediatric emergency services or specialty care. In view of this challenge, this study first sought to map the prevailing geographical accessibility to children's hospitals and, second, to model the hospital beds per capita for each hospital's service area within the state of Texas. The results showed disparities in accessing emergency pediatric care, especially in rural areas. However, despite major metro areas recording better geographical accessibility to pediatric healthcare, residents in these areas may experience limited hospital bed availability. The findings indicate an urgent need for more pediatric healthcare services in rural Texas. Given the increasing population growth in metro areas and their surroundings, there is also a need for the expansion of healthcare infrastructure in these areas.

Epidemiological behaviour and interventions of malaria in Niger, 2010-2019: a time-series analysis of national surveillance data

BACKGROUND

Malaria remains a significant public health concern in Niger, with the number of cases increasing from 592,334 in 2000 to 3,138,696 in 2010. In response, a concerted campaign against the disease has been initiated. However, the implementation of these malaria interventions and their association with epidemiological behaviour remains unclear.

METHODS

A time-series study was conducted in Niger from 2010 to 2019. Multiple data sources concerning malaria were integrated, encompassing national surveillance data, Statistic Yearbook, targeted malaria control interventions, and meteorological data. Incidence rate, mortality rate, and case fatality ratio (CFR) by different regions and age groups were analysed. Joinpoint regression models were used to estimate annual changes in malaria. The changes in coverage of malaria interventions were evaluated.

RESULTS

Between 2010 to 2019, the incidence rate of malaria decreased from 249.43 to 187.00 cases per 1,000 population in Niger. Niamey had a high annual mean incidence rate and the lowest CFR, while Agadez was on the contrary. Joinpoint regression analysis revealed a declining trend in malaria incidence for all age groups except the 10-24 years group, and the mortality rate and the CFR initially decreased followed by an increase in all age groups. Niger has implemented a series of malaria interventions, with the major ones being scaled up to larger populations during the study period.

CONCLUSIONS

The scale-up of multi-interventions in Niger has significantly reduced malaria incidence, but the rise in mortality rate and CFR addresses the challenges in malaria control and elimination. Malaria endemic countries should enhance surveillance of malaria cases and drug resistance in Plasmodium, improve diagnosis and treatment, expand the population coverage of insecticide-treated bed nets and seasonal malaria chemoprevention, and strengthen the management of severe malaria cases.

Estimating the effects of COVID-19 on essential health services utilization in Uganda and Bangladesh using data from routine health information systems

Background

Since March 2020, the coronavirus disease 2019 (COVID-19) pandemic has been a major shock to health systems across the world. We examined national usage patterns for selected basic, essential health services, before and during the COVID-19 pandemic in Uganda and Bangladesh, to determine whether COVID-19 affected reporting of service utilization and the use of health services in each country.

Methods

We used routine health information system data since January 2017 to analyze reporting and service utilization patterns for a variety of health services. Using time series models to replicate pre-COVID-19 trajectories over time we estimated what levels would have been observed if COVID-19 had not occurred during the pandemic months, starting in March 2020. The difference between the observed and predicted levels is the COVID-19 effect on health services.

Results

The time trend models for Uganda and Bangladesh closely replicated the levels and trajectories of service utilization during the 38 months prior to the COVID-19 pandemic. Our results indicate that COVID-19 had severe effects across all services, particularly during the first months of the pandemic, but COVID-19 impacts on health services and subsequent recovery varied by service type. In general, recovery to expected levels was slow and incomplete across the most affected services.

Conclusion

Our analytical approach based on national information system data could be very useful as a form of surveillance for health services disruptions from any cause leading to rapid responses from health service managers and policymakers.

Impacts of seasonal flooding on geographical access to maternal healthcare in the Barotse Floodplain, Zambia

BACKGROUND

Seasonal floods pose a commonly-recognised barrier to women's access to maternal services, resulting in increased morbidity and mortality. Despite their importance, previous GIS models of healthcare access have not adequately accounted for floods. This study developed new methodologies for incorporating flood depths, velocities, and extents produced with a flood model into network- and raster-based health access models. The methodologies were applied to the Barotse Floodplain to assess flood impact on women's walking access to maternal services and vehicular emergency referrals for a monthly basis between October 2017 and October 2018.

METHODS

Information on health facilities were acquired from the Ministry of Health. Population density data on women of reproductive age were obtained from the High Resolution Settlement Layer. Roads were a fusion of OpenStreetMap and data manually delineated from satellite imagery. Monthly information on floodwater depth and velocity were obtained from a flood model for 13-months. Referral driving times between delivery sites and EmOC were calculated with network analysis. Walking times to the nearest maternal services were calculated using a cost-distance algorithm.

RESULTS

The changing distribution of floodwaters impacted the ability of women to reach maternal services. At the peak of the dry season (October 2017), 55%, 19%, and 24% of women had walking access within 2-hrs to their nearest delivery site, EmOC location, and maternity waiting shelter (MWS) respectively. By the flood peak, this dropped to 29%, 14%, and 16%. Complete inaccessibility became stark with 65%, 76%, and 74% unable to access any delivery site, EmOC, and MWS respectively. The percentage of women that could be referred by vehicle to EmOC from a delivery site within an hour also declined from 65% in October 2017 to 23% in March 2018.

CONCLUSIONS

Flooding greatly impacted health access, with impacts varying monthly as the floodwave progressed. Additional validation and application to other regions is still needed, however our first results suggest the use of a hydrodynamic model permits a more detailed representation of floodwater impact and there is great potential for generating predictive models which will be necessary to consider climate change impacts on future health access.

Health worker compliance with severe malaria treatment guidelines in the context of implementing pre-referral rectal artesunate in the Democratic Republic of the Congo, Nigeria, and Uganda: An operational study

BACKGROUND

For a full treatment course of severe malaria, community-administered pre-referral rectal artesunate (RAS) should be completed by post-referral treatment consisting of an injectable antimalarial and oral artemisinin-based combination therapy (ACT). This study aimed to assess compliance with this treatment recommendation in children under 5 years.

METHODS AND FINDINGS

This observational study accompanied the implementation of RAS in the Democratic Republic of the Congo (DRC), Nigeria, and Uganda between 2018 and 2020. Antimalarial treatment was assessed during admission in included referral health facilities (RHFs) in children under 5 with a diagnosis of severe malaria. Children were either referred from a community-based provider or directly attending the RHF. RHF data of 7,983 children was analysed for appropriateness of antimalarials; a subsample of 3,449 children was assessed additionally for dosage and method of ACT provision (treatment compliance). A parenteral antimalarial and an ACT were administered to 2.7% (28/1,051) of admitted children in Nigeria, 44.5% (1,211/2,724) in Uganda, and 50.3% (2,117/4,208) in DRC. Children receiving RAS from a community-based provider were more likely to be administered post-referral medication according to the guidelines in DRC (adjusted odds ratio (aOR) = 2.13, 95% CI 1.55 to 2.92, P < 0.001), but less likely in Uganda (aOR = 0.37, 95% CI 0.14 to 0.96, P = 0.04) adjusting for patient, provider, caregiver, and other contextual factors. While in DRC, inpatient ACT administration was common, ACTs were often prescribed at discharge in Nigeria (54.4%, 229/421) and Uganda (53.0%, 715/1,349). Study limitations include the unfeasibility to independently confirm the diagnosis of severe malaria due to the observational nature of the study.

CONCLUSIONS

Directly observed treatment was often incomplete, bearing a high risk for partial parasite clearance and disease recrudescence. Parenteral artesunate not followed up with oral ACT constitutes an artemisinin monotherapy and may favour the selection of resistant parasites. In connection with the finding that pre-referral RAS had no beneficial effect on child survival in the 3 study countries, concerns about an effective continuum of care for children with severe malaria seem justified. Stricter compliance with the WHO severe malaria treatment guidelines is critical to effectively manage this disease and further reduce child mortality.

TRIAL REGISTRATION

ClinicalTrials.gov (NCT03568344).

Under age five children survival times in Nigeria: a Bayesian spatial modeling approach

BACKGROUND

Nigeria is among the top five countries in the world with the highest under-five mortality rates. In addition to the general leading causes of under-five mortality, studies have shown that disparity in sociocultural values and practices across ethnic groups in Nigeria influence child survival, thus there is a need for scientific validation. This study quantified the survival probabilities and the impact of socioeconomic and demographic factors, proximate and biological determinants, and environmental factors on the risk of under-five mortality in Nigeria.

METHODS

The Kaplan-Meier survival curve, Nelson Aalen hazard curve, and components survival probabilities were estimated. The Exponential, Gamma, Log-normal, Weibull, and Cox hazard models in a Bayesian mixed effect hierarchical hazard modeling framework with spatial components were considered, and the Deviance and Watanabe Akaike information criteria were used to select the best model for inference. A [Formula: see text] level of significance was assumed throughout this work. The 2018 Nigeria Demographic and Health Survey dataset was used, and the outcome variable was the time between birth and death or birth and the date of interview for children who were alive on the day of the interview.

RESULTS

Findings show that the probability of a child dying within the first two months is 0.04, and the probability of a boy child dying before attaining age five is 0.106, while a girl child is 0.094 probability. Gender, maternal education, household wealth status, source of water and toilet facility, residence, mass media, frequency of antenatal and postnatal visits, marital status, place of delivery, multiple births, who decide healthcare use, use of bednet are significant risk factors of child mortality in Nigeria. The mortality risk is high among the maternal age group below 24 and above 44years, and birth weight below 2.5Kg and above 4.5Kg. The under-five mortality risk is severe in Kebbi, Kaduna, Jigawa, Adamawa, Gombe, Kano, Kogi, Nasarawa, Plateau, and Sokoto states in Nigeria.

CONCLUSION

This study accentuates the need for special attention for the first two months after childbirth as it is the age group with the highest expected mortality. A practicable way to minimize death in the early life of children is to improve maternal healthcare service, promote maternal education, encourage delivery in healthcare facilities, positive parental attitude to support multiple births, poverty alleviation programs for the less privileged, and a prioritized intervention to Northern Nigeria.

Distance to Healthcare Facility and Lady Health Workers’ Visits Reduce Malnutrition in under Five Children: A Case Study of a Disadvantaged Rural District in Pakistan

This study accesses the impact of lady health worker (LHWs) visits in the community and distance to a healthcare facility on the nutritional status of under-five children. Additionally, it explores the perceptions and attitudes of the community about the performance of LHWs. A self-administered instrument was applied to gather data on different parameters, such as children’s height, age, weight, and socioeconomic status from 384 rural households in a marginalized district of Punjab province with the help of a purposive random sampling technique. The binary logistic regression model was employed for the computation of the probability of malnutrition. The prevalences of stunting, underweight children, and wasting in the district were 34.8%, 46.1%, and 15.5%, respectively. The logistic results illustrate that those households in which LHW visits occur regularly within 15 days (OR = 0.28 with 95% CI: 0.09–0.82) have a lower probability of malnutrition prevalence among their children. The distance to the health facility shows that the odds of malnutrition were higher from 3–4 Kilometers (Km) (OR = 2.61, 95% CI: 0.85–8.14), and odds were also higher for the ≥5 km category (OR = 2.88, 95% CI: 0.94–8.82). Children from richer families had lower chances of being malnourished (OR = 0.28, 95% CI: 0.07–1.14). Furthermore, the respondents show a positive attitude towards LHWs. They have given the first rank to their performance being beneficial to mothers and childcare, especially on checkups and safe deliveries, while they have shown negative responses and given lower ranks to their performance due to irregular visits (6th rank) and poor community awareness (7th rank). We conclude that LHWs’ regular visits to targeted households and less distance to healthcare facilities reduce the malnutrition risk in under-five children.

Rethinking integrated service delivery for malaria

Despite worldwide efforts and much progress toward malaria control, declines in malaria morbidity and mortality have hit a plateau. While many nations achieved significant malaria suppression or even elimination, success has been uneven, and other nations have made little headway-or even lost ground in this battle. These alarming trends threaten to derail the attainment of global targets for malaria control. Among the challenges impeding success in malaria reduction, many strategies center malaria as a set of technical problems in commodity development and delivery. Yet, this narrow perspective overlooks the importance of strong health systems and robust healthcare delivery. This paper argues that strategies that move the needle on health services and behaviors offer a significant opportunity to achieve malaria control through a comprehensive approach that integrates malaria with broader health services efforts. Indeed, malaria may serve as the thread that weaves integrated service delivery into a path forward for universal health coverage. Using key themes identified by the "Rethinking Malaria in the Context of COVID-19" effort through engagement with key stakeholders, we provide recommendations for pursuing integrated service delivery that can advance malaria control via strengthening health systems, increasing visibility and use of high-quality data at all levels, centering issues of equity, promoting research and innovation for new tools, expanding knowledge on effective implementation strategies for interventions, making the case for investing in malaria among stakeholders, and engaging impacted communities and nations.

Comparing absolute and relative distance and time travel measures of geographic access to healthcare facilities in rural Haiti

INTRODUCTION

While travel distance and time are important proxies of physical access to health facilities, obtaining valid measures with an appropriate modelling method remains challenging in many settings. We compared five measures of geographic accessibility in Haiti, producing recommendations that consider available analytic resources and geospatial goals.

METHODS

Eight public hospitals within the ministry of public health and population were included. We estimated distance and time between hospitals and geographic centroids of Haiti's section communes and population-level accessibility. Geographic feature data were obtained from public administrative databases, academic research databases and government satellites. We used validated geographic information system methods to produce five geographic access measures: (1) Euclidean distance (ED), (2) network distance (ND), (3) network travel time (NTT), (4) AccessMod 5 (AM5) distance (AM5D) and (5) AM5 travel time (AM5TT). Relative ranking of section communes across the measures was assessed using Pearson correlation coefficients, while mean differences were assessed using analysis of variance (ANOVA) and pairwise t-tests.

RESULTS

All five geographic access measures were highly correlated (range: 0.78-0.99). Of the distance measures, ED values were consistently the shortest, followed by AM5D values, while ND values were the longest. ND values were as high as 2.3 times ED values. NTT models generally produced longer travel time estimates compared with AM5TT models. ED consistently overestimated population coverage within a given threshold compared with ND and AM5D. For example, population-level accessibility within 15 km of the nearest studied hospital in the Center department was estimated at 68% for ED, 50% for AM5D and 34% for ND.

CONCLUSION

While the access measures were highly correlated, there were significant differences in the absolute measures. Consideration of the benefits and limitations of each geospatial measure together with the intended purpose of the estimates, such as relative proximity of patients or service coverage, are key to guiding appropriate use.

Maternal social support and health facility delivery in Southwest Ethiopia

BACKGROUND

Maternal mortality continues to decrease in the world but remain the most important health problems in low-income countries. Although evidence indicates that social support is an important factor influencing health facility delivery, it has not been extensively studied in Ethiopia. Therefore, this study aimed to assess the effect of maternal social support and related factors on health facility delivery in southwest Ethiopia.

METHODS

A cross-sectional survey data on 3304 women aged 15-47 years in three districts of Ethiopia, were analyzed. Using multivariable logistic regression, we assessed the association between health facility birth, social support, and socio-demography variables. Adjusted odds ratios with 95% confidence intervals were used to identify statistically significant associations at 5% alpha level.

RESULT

Overall, 46.9% of women delivered at health facility in their last pregnancy. Average travel time from closest health facility (AOR: 1.51, 95% CI 1.21 to 2.90), mean perception score of health facility use (AOR: 1.83, 95% CI 1.44 to 2.33), involvement in final decision to identify their place of childbirth (AOR: 2.12, 95% CI 1.73 to 2.58) had significantly higher odds of health facility childbirth. From social support variables, women who perceived there were family members and husband to help them during childbirth (AOR: 3.62, 95% CI 2.74 to 4.79), women who received continuous support (AOR: 1.97, 95% CI 1.20 to 3.23), women with companions for facility visits (AOR: 1.63, 95% CI 1.34 to 2.00) and women who received support from friends (AOR: 1.62, 95% CI 1.16 to 3.23) had significantly higher odds of health facility childbirth.

CONCLUSIONS

Social support was critical to enhance health facility delivery, especially if women's close ties help facility delivery. An intervention to increase facility delivery uptake should target not only the women's general social supports, but also continuous support during childbirth from close ties including family members and close friends as these are influential in place of childbirth. Also actions that increase women's healthcare decision could be effective in improving health facility delivery.

Tweedie Model for Predicting Factors Associated with Distance Traveled to Access Inpatient Services in Kenya

Aim. This study aims to examine which factors influence the distance traveled by patients for inpatient care in Kenya. Methods. We used data from the fourth round of the Kenya Household Health Expenditure and Utilization survey. Our dependent variable was the self-reported distance traveled by patients to access inpatient care at public health facilities. As the clustered data were correlated, we used the generalized estimating equations approach with an exchangeable correlation under a Tweedie distribution. To select the best-fit covariates for predicting distance, we adopted a variable selection technique using the $QI{C}_u$ and $R^2$ criteria, wherein the lowest (highest) value for the former (latter) is preferred. Results. Using data for 451 participants from 47 counties, we found that three-fifths were admitted between 1 and 5 days, two-thirds resided in rural areas, and 90% were satisfied with the facilities’ service. Wealth quintiles were evenly distributed across respondents. Most admissions (81%) comprised $<$ 15, $>$ 65, and 25–54 years. Many households were of medium size (4–6 members) and had low education level (48%), and nine-tenths had no access to insurance. While two-thirds reported employment-based income, the same number reported not having cash to pay for inpatient services; 6 out of 10 paid over 3000 KES. Thus, differences in employment, ability to pay, and household size influence the distance traveled to access government healthcare facilities in Kenya. Interpretation. Low-income individuals more likely have large households and live in rural areas and, thus, are forced to travel farther to access inpatient care. Unlike the unemployed, the employed may have better socioeconomic status and possibly live near inpatient healthcare facilities, thereby explaining their short distances to access these services. Policymakers must support equal access to inpatient services, prioritize rural areas, open job opportunities, and encourage smaller families.

Determinants of Modern Paediatric Healthcare Seeking in Rural Côte d’Ivoire

Objectives: To determine factors that influence healthcare seeking among children with fatal and non-fatal health problems.

Methods: Last disease episodes of surviving children and fatal outcomes of children under 5 years of age were investigated by means of an adapted social autopsy questionnaire administered to main caregivers. Descriptive analysis and logistic models were employed to identify key determinants of modern healthcare use.

Results: Overall, 736 non-fatal and 82 fatal cases were assessed. Modern healthcare was sought for 63.9% of non-fatal and 76.8% of fatal cases, respectively. In non-fatal cases, young age, caregiver being a parent, secondary or higher education, living <5 km from a health facility, and certain clinical signs (i.e., fever, severe vomiting, inability to drink, convulsion, and inability to play) were positively associated with modern healthcare seeking. In fatal cases, only signs of lower respiratory disease were positively associated with modern healthcare seeking. A lack of awareness regarding clinical danger signs was identified in both groups.

Conclusion: Interventions promoting prompt healthcare seeking and the recognition of danger signs may help improve treatment seeking in rural settings of Côte d’Ivoire and can potentially help further reduce under-five mortality.

Enhancing Public Participation in Public Health Offerings: Patient Preferences for Facilities in the Western Cape Province Using a Discrete Choice Experiment

Understanding patients’ preferences for health facilities could help decision makers in designing patient-centered services. Therefore, this study aims to understand how patients’ willingness to trade for certain attributes affects the choice of public health facilities in the Western Cape province of Cape Town, South Africa. A discrete choice experiment was conducted in two community day centers (CDCs). Patients repetitively chose between two hypothetical health facilities that differed in six attributes: distance to facility, treatment by doctors vs. nurses, confidentiality during treatment, availability of medication, first visit (drop-in) waiting times, and appointment waiting times. The sample consisted of 463 participants. The findings showed that availability of medication (50.5%), appointment waiting times (19.5%), and first visit waiting times (10.2%) were the most important factors for patients when choosing a health facility. In addition, respondents preferred shorter appointment and first visit waiting times (<2 h). These results identified important characteristics in choosing public health facilities in Cape Town. These public health facilities could be improved by including patient voices to inform operational and policy decisions in a low-income setting.

Rural-Urban Differences: Using Finer Geographic Classifications to Reevaluate Distance and Choice of Health Services in Malawi

There is no universal understanding of what defines urban or rural areas nor criteria for differentiating within these. When assessing access to health services, traditional urban-rural dichotomies may mask substantial variation. We use geospatial methods to link household data from the 2015-2016 Malawi Demographic Health Survey to health facility data from the Malawi Service Provision Assessment and apply a new proposed four-category classification of geographic area (urban major metropolitan area, urban township, rural, and remote) to evaluate households' distance to, and choice of, primary, secondary, and tertiary health care in Malawi. Applying this new four-category definition, approximately 3.8 million rural- and urban-defined individuals would be reclassified into new groups, nearly a quarter of Malawi's 2015 population. There were substantial differences in distance to the nearest facility using this new categorization: remote households are (on average) an additional 5 km away from secondary and tertiary care services versus rural households. Health service choice differs also, particularly in urban areas, a distinction that is lost when using a simple binary classification: those living in major metropolitan households have a choice of five facilities offering comprehensive primary care services within a 10-km zone, whereas urban township households have no choice, with only one such facility within 10 km. Future research should explore how such expanded classifications can be standardized and used to strengthen public health and demographic research.

Ethnic diversity and mortality in northwest Burkina Faso: An analysis of the Nouna health and demographic surveillance system from 2000 to 2012

Ethnic diversity has been a topic of contention across the globe, contrasted with economic development, social security, and political stability. The link between health and ethnic diversity is not yet well established especially in low-middle- income countries. Our study aims to explore the association between ethnic diversity and all-cause mortality in rural areas of Burkina Faso. We used data from the Nouna Health & Demographic Surveillance System (HDSS) collected between 2000 and 2012. To derive Standardized Mortality Ratios (SMR), the observed number of deaths was compared to the expected deaths based on the entire HDSS taking into account sex, age, rainy season, calendar year, and village. SMR were calculated for ethnic and religious diversity on a village level (using the Simpson Index), sub-region, wealth, and distance to Healthcare Facilities (HCF). Furthermore, we modeled SMR with a multilevel random intercept Poisson regression considering individual ethnic and religious groups in addition to the above-mentioned village-level information. Village wealth (poorest fifth: SMR 1.07; 95% CI: 1.02-1.13, richest fifth: SMR 0.85; 95% CI: 0.82-0.88), distance to HCF (within the village: SMR 0.88; 95% CI: 0.85-0.91, further than 5km: SMR 1.13; 95% CI: 1.10-1.16), and sub-region showed significant associations with overall mortality. Villages belonging to the third with the highest ethnic diversity had lowered SMR (0.86; 95% CI: 0.84-0.89) compared to the entire HDSS, while those belonging to the lowest diversity third yielded elevated SMR (1.13; 95% CI: 1.09-1.17). The multilevel model confirmed the association. Our study showed that historically established ethnic diversity in rural areas of Burkina Faso was associated with lower all-cause mortality. Generally, the literature suffers from a lack of standardization in defining ethnic diversity, along with measuring it. More research is needed to understand this relation and to establish it in different settings.

Guiding placement of health facilities using multiple malaria criteria and an interactive tool

BACKGROUND

Access to healthcare is important in controlling malaria burden and, as a result, distance or travel time to health facilities is often a significant predictor in modelling malaria prevalence. Adding new health facilities may reduce overall travel time to health facilities and may decrease malaria transmission. To help guide local decision-makers as they scale up community-based accessibility, the influence of the spatial allocation of new health facilities on malaria prevalence is evaluated in Bunkpurugu-Yunyoo district in northern Ghana. A location-allocation analysis is performed to find optimal locations of new health facilities by separately minimizing three district-wide objectives: malaria prevalence, malaria incidence, and average travel time to health facilities.

METHODS

Generalized additive models was used to estimate the relationship between malaria prevalence and travel time to the nearest health facility and other geospatial covariates. The model predictions are then used to calculate the optimisation criteria for the location-allocation analysis. This analysis was performed for two scenarios: adding new health facilities to the existing ones, and a hypothetical scenario in which the community-based healthcare facilities would be allocated anew. An interactive web application was created to facilitate efficient presentation of this analysis and allow users to experiment with their choice of health facility location and optimisation criteria.

RESULTS

Using malaria prevalence and travel time as optimisation criteria, two locations that would benefit from new health facilities were identified, regardless of scenarios. Due to the non-linear relationship between malaria incidence and prevalence, the optimal locations chosen based on the incidence criterion tended to be inequitable and was different from those based on the other optimisation criteria.

CONCLUSIONS

This study findings underscore the importance of using multiple optimisation criteria in the decision-making process. This analysis and the interactive application can be repurposed for other regions and criteria, bridging the gap between science, models and decisions.

The effects of geographical accessibility to health facilities on antenatal care and delivery services utilization in Benin: a cross-sectional study

Background

The world is making progress toward achieving maternal and child health (MCH) related components of the Sustainable Development Goals. Nevertheless, the progress of many countries in Sub-Saharan Africa is lagging. Geographical accessibility from residence to health facilities is considered a major obstacle hampering the use of appropriate MCH services. Benin, a country where the southern and northern parts belong to different geographical zones, has among the highest maternal mortality rate in the world. Adequate use of MCH care is important to save lives of women and their babies. This study assessed the effect of geographical accessibility to health facilities on antenatal care and delivery services utilization in Benin, with an emphasis on geographical zones.

Methods

We pooled two rounds of Benin Demographic and Health Surveys (BDHS). The sample included 18,105 women aged 15–49 years (9111 from BDHS-2011/2012 and 8994 from BDHS-2017/2018) who had live births within five years preceding the surveys. We measured the distance and travel time from residential areas to the closest health center by merging the BDHS datasets with Benin’s geographic information system data. Multivariate logistic regression analysis was performed to estimate the effect of geographical access on pregnancy and delivery services utilization. We conducted a propensity score-matching analysis to check for robustness.

Results

Regression results showed that the distance to the closest health center had adverse effects on the likelihood of a woman receiving appropriate maternal healthcare. The estimates showed that one km increase in straight-line distance to the closest health center reduces the odds of the woman receiving at least one antenatal care by 0.042, delivering in facility by 0.092, and delivering her baby with assistance of skilled birth attendants by 0.118. We also confirmed the negative effects of travel time and altitude of women’s residence on healthcare utilization. Nonetheless, these effects were mainly seen in the northern part of Benin.

Conclusions

Geographical accessibility to health facilities is critically important for the utilization of antenatal care and delivery services, particularly in the northern part of Benin. Improving geographical accessibility, especially in rural areas, is significant for further use of maternal health care in Benin.

Maternal and neonatal mortality rates are still high in many countries in Sub-Saharan Africa. Antenatal care (ANC) visits and institutional delivery with skilled birth attendants are important to prevent maternal and neonatal deaths. Nevertheless, women’s utilization of ANC and delivery services has decreased recently in Benin, a country where the southern and northern parts belong to different geographical zones.

Geographical accessibility from residence to health facilities is considered a major obstacle hampering the use of appropriate maternal healthcare. This study assessed the effect of geographical accessibility on ANC and delivery services utilization in Benin by considering the geographical characteristics.

We used the two rounds of the Benin Demographic and Health Survey 2011/2012 and 2017/2018 and conducted regression analysis.

This study has three important findings: (1) We confirmed adverse effects of distance and travel time on the likelihood of a women receiving appropriate ANC and delivery services in Benin, but this effect was mainly observed in the northern part; (2) Distance and travel time to health facilities had a negative effect on the use of at least one ANC but no significant effect for four or more ANC; (3) Regarding the threshold of distance, we confirmed that women living within 5 km from the closest health center were more likely to use maternal healthcare compared to their counterparts.

In conclusion, geographical accessibility to health facilities is critically important for the utilization of antenatal care and delivery services, particularly in the northern part of Benin.

Walking and perceived lack of safety: Correlates and association with health outcomes for people living with HIV in rural Zambia

INTRODUCTION

Geographic inaccessibility disproportionately affects health outcomes of rural populations due to lack of suitable transport, prolonged travel time, and poverty. Rural patients are left with few transport options to travel to a health facility. One common option is to travel by foot, which may present additional challenges, such as perceived lack of safety while transiting. We examined the correlates of perceived lack of safety when walking to a health facility and its association with treatment and psychosocial outcomes among adults living with HIV.

METHODS

Data were collected from 101 adults living with HIV in Eastern Province, Zambia. All participants were receiving antiretroviral therapy at one of two health clinics. Perceived lack of safety was measured by asking respondents whether they felt unsafe traveling to and from the health facility in which they were receiving their HIV care. Outcomes included medication adherence, perceived stress, hope for the future, and barriers to pill taking. Linear and logistic regression methods were used to examine the correlates of perceived safety and its association with health outcomes.

RESULTS

Being older, a woman, having a primary education, living farther from a health facility, traveling longer to reach a health facility, and owing money were associated with higher likelihood of feeling unsafe when traveling by foot to health facility. Perceived lack of safety was associated with medication nonadherence, higher level of stress, lower level of agency, and more barriers to pill taking.

CONCLUSIONS

Perceived lack of safety when traveling by foot to a health facility may be a barrier to better treatment and psychosocial outcomes, especially among rural patients. Practitioners and policymakers should consider implementation of differentiated HIV service delivery models to reduce frequent travel to health facilities and to alleviate ART patients' worry about lack of safety when traveling by foot to a health facility.

The effect of distance on maternal institutional delivery choice: Evidence from Malawi

In many low- and middle-income countries, geographical accessibility continues to be a barrier to health care utilization. In this paper, we aim to better understand the full relationship between distance to providers and utilization of maternal delivery services. We address three methodological challenges: non-linear effects between distance and utilization; unobserved heterogeneity through non-random distance "assignment"; and heterogeneous effects of distance. Linking Malawi Demographic Health Survey household data to Service Provision Assessment facility data, we consider distance as a continuous treatment variable, estimating a Dose-Response Function based on generalized propensity scores, allowing exploration of non-linearities in the effect of an increment in distance at different distance exposures. Using an instrumental variables approach, we examine the potential for unobserved differences between women residing at different distances to health facilities. Our results suggest distance significantly reduces the probability of having a facility delivery, with evidence of non-linearities in the effect. The negative relationship is shown to be particularly strong for women with poor health knowledge and lower socio-economic status, with important implications for equity. We also find evidence of potential unobserved confounding, suggesting that methods that ignore such confounding may underestimate the effect of distance on the utilization of health services.

Patterns of child mortality in rural area of Burkina Faso: evidence from the Nanoro health and demographic surveillance system (HDSS)

Background

Half of global child deaths occur in sub-Saharan Africa. Understanding child mortality patterns and risk factors will help inform interventions to reduce this heavy toll. The Nanoro Health and Demographic Surveillance System (HDSS), Burkina Faso was described previously, but patterns and potential drivers of heterogeneity in child mortality in the district had not been studied. Similar studies in other districts indicated proximity to health facilities as a risk factor, usually without distinction between facility types.

Methods

Using Nanoro HDSS data from 2009 to 2013, we estimated the association between under-5 mortality and proximity to inpatient and outpatient health facilities, seasonality of death, age group, and standard demographic risk factors.

Results

Living in homes 40–60 min and > 60 min travel time from an inpatient facility was associated with 1.52 (95% CI: 1.13–2.06) and 1.74 (95% CI: 1.27–2.40) greater hazard of under-5 mortality, respectively, than living in homes < 20 min from an inpatient facility. No such association was found for outpatient facilities. The wet season (July–November) was associated with 1.28 (95% CI: 1.07, 1.53) higher under-5 mortality than the dry season (December–June), likely reflecting the malaria season.

Conclusions

Our results emphasize the importance of geographical proximity to health care, distinguish between inpatient and outpatient facilities, and also show a seasonal effect, probably driven by malaria.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11483-4.

Health inequities and clustering of fever, acute respiratory infection, diarrhoea and wasting in children under five in low- and middle-income countries: a Demographic and Health Surveys analysis

BACKGROUND

Pneumonia, diarrhoea and malaria are responsible for over one third of all deaths in children under the age of 5 years in low and middle sociodemographic index countries; many of these deaths are also associated with malnutrition. We explore the co-occurrence and clustering of fever, acute respiratory infection, diarrhoea and wasting and their relationship with equity-relevant variables.

METHODS

Multilevel, multivariate Bayesian logistic regression models were fitted to Demographic and Health Survey data from over 380,000 children in 39 countries. The relationship between outcome indicators (fever, acute respiratory infection, diarrhoea and wasting) and equity-relevant variables (wealth, access to health care and rurality) was examined. We quantified the geographical clustering and co-occurrence of conditions and a child's risk of multiple illnesses.

RESULTS

The prevalence of outcomes was very heterogeneous within and between countries. There was marked spatial clustering of conditions and co-occurrence within children. For children in the poorest households and those reporting difficulties accessing healthcare, there were significant increases in the probability of at least one of the conditions in 18 of 21 countries, with estimated increases in the probability of up to 0.23 (95% CrI, 0.06-0.40).

CONCLUSIONS

The prevalence of fever, acute respiratory infection, diarrhoea and wasting are associated with equity-relevant variables and cluster together. Via pathways of shared aetiology or risk, those children most disadvantaged disproportionately suffer from these conditions. This highlights the need for horizontal approaches, such as integrated community case management, with a focus on equity and targeted to those most at need.

Modeling the relationship between malaria prevalence and insecticide-treated bed net coverage in Nigeria using a Bayesian spatial generalized linear mixed model with a Leroux prior

OBJECTIVES

To evaluate malaria transmission in relation to insecticide-treated net (ITN) coverage in Nigeria.

METHODS

We used an exploratory analysis approach to evaluate variation in malaria transmission in relation to ITN distribution in 1,325 Demographic and Health Survey clusters in Nigeria. A Bayesian spatial generalized linear mixed model with a Leroux conditional autoregressive prior for the random effects was used to model the spatial and contextual variation in malaria prevalence and ITN distribution after adjusting for environmental variables.

RESULTS

Spatial smoothed maps showed the nationwide distribution of malaria and ITN. The distribution of ITN varied significantly across the 6 geopolitical zones (p<0.05). The North-East had the least ITN distribution (0.196±0.071), while ITN distribution was highest in the South-South (0.309±0.075). ITN coverage was also higher in rural areas (0.281±0.074) than in urban areas (0.240±0.096, p<0.05). The Bayesian hierarchical regression results showed a non-significant negative relationship between malaria prevalence and ITN coverage, but a significant spatial structured random effect and unstructured random effect. The correlates of malaria transmission included rainfall, maximum temperature, and proximity to water.

CONCLUSIONS

Reduction in malaria transmission was not significantly related to ITN coverage, although much could be achieved in attempts to curtail malaria transmission through enhanced ITN coverage. A multifaceted and integrated approach to malaria control is strongly advocated.

Multidrug-resistant enteric pathogens in older children and adults with diarrhea in Bangladesh: epidemiology and risk factors

BACKGROUND

Antimicrobial resistance (AMR) is a global public health threat and is increasingly prevalent among enteric pathogens in low- and middle-income countries (LMICs). However, the burden of multidrug-resistant organisms (MDROs) in older children, adults, and elderly patients with acute diarrhea in LMICs is poorly understood. This study's aim was to characterize the prevalence of MDR enteric pathogens isolated from patients with acute diarrhea in Dhaka, Bangladesh, and assess a wide range of risk factors associated with MDR.

METHODS

This study was a secondary analysis of data collected from children over 5 years, adults, and elderly patients with acute diarrhea at the International Centre for Diarrhoeal Disease Research, Bangladesh Dhaka Hospital between March 2019 and March 2020. Clinical, historical, socio-environmental information, and a stool sample for culture and antimicrobial susceptibility testing were collected from each patient. Univariate statistics and multiple logistic regression were used to assess the prevalence of MDR among enteric pathogens and the association between independent variables and presence of MRDOs among culture-positive patients.

RESULTS

A total of 1198 patients had pathogens isolated by stool culture with antimicrobial susceptibility results. Among culture-positive patients, the prevalence of MDR was 54.3%. The prevalence of MDR was highest in Aeromonas spp. (81.5%), followed by Campylobacter spp. (72.1%), Vibrio cholerae (28.1%), Shigella spp. (26.2%), and Salmonella spp. (5.2%). Factors associated with having MDRO in multiple logistic regression included longer transport time to hospital (>90 min), greater stool frequency, prior antibiotic use prior to hospital presentation, and non-flush toilet use. However, pseudo-R2 was low 0.086, indicating that other unmeasured variables need to be considered to build a more robust predictive model of MDR.

CONCLUSIONS

MDR enteric pathogens were common in this study population with clinical, historical, and socio-environmental risk factors associated with MDROs. These findings may help guide clinical decision-making regarding antibiotic use and selection in patients at greatest risk of complications due to MDROs. Further prospective research is urgently needed to determine what additional factors place patients at greatest risk of MDRO, and the best strategies to mitigate the spread of MDR in enteric pathogens.

Household factors and under-five mortality in Bankass, Mali: results from a cross-sectional survey

BACKGROUND

Rural parts of Mali carry a disproportionate burden of the country's high under-five mortality rate. A range of household factors are associated with poor under-five health in resource-limited settings. However, it is unknown which most influence the under-five mortality rate in rural Mali. We aimed to describe household factors associated with under-five mortality in Bankass, a remote region in central Mali.

METHODS

We analysed baseline household survey data from a trial being conducted in Bankass. The survey was administered to households between December 2016 and January 2017. Under-five deaths in the five years prior to baseline were documented along with detailed information on household factors and women's birth histories. Factors associated with under-five mortality were analysed using Cox regression.

RESULTS

Our study population comprised of 17,408 under-five children from 8322 households. In the five years prior to baseline, the under-five mortality rate was 152.6 per 1000 live births (158.8 and 146.0 per 1000 live births for males and females, respectively). Living a greater distance from a primary health center was associated with a higher probability of under-five mortality for both males (adjusted hazard ratio [aHR] 1.53 for ≥10 km versus < 2 km, 95% confidence interval [CI] 1.25-1.88) and females (aHR 1.59 for ≥10 km versus < 2 km, 95% CI 1.27-1.99). Under-five male mortality was additionally associated with lower household wealth quintile (aHR 1.47 for poorest versus wealthiest, 95%CI 1.21-1.78), lower reading ability among women of reproductive age in the household (aHR 1.73 for cannot read versus can read, 95%CI 1.04-2.86), and living in a household with access to electricity (aHR 1.16 for access versus no access, 95%CI 1.00-1.34).

CONCLUSIONS

U5 mortality is very high in Bankass and is associated with living a greater distance from healthcare and several other household factors that may be amenable to intervention or facilitate program targeting.

Methods of Measuring Spatial Accessibility to Health Care in Uganda

Ensuring everyone has access to health care regardless of demographic, geographic and social economic status is a key component of universal health coverage. In sub-Saharan Africa, where populations are often sparsely distributed and services scarcely available, reducing distances or travel time to facilities is key in ensuring access to health care. This chapter traces the key concepts in measuring spatial accessibility by reviewing six methods—Provider-to-population ratio, Euclidean distance, gravity models, kernel density, network analysis and cost distance analysis—that can be used to model spatial accessibility. The advantages and disadvantages of using each of these models are also laid out, with the aim of choosing a model that can be used to capture spatial access. Using an example from Uganda, a cost distance analysis is used to model travel time to the nearest primary health care facility. The model adjusts for differences in land use, weather patterns and elevation while also excluding barriers such as water bodies and protected areas in the analysis. Results show that the proportion of population within 1-h travel times for the 13 regions in the country varies from 64.6% to 96.7% in the dry period and from 61.1% to 96.3% in the wet period. The model proposed can thus be used to highlight disparities in spatial accessibility, but as we demonstrate, care needs to be taken in accurate assembly of data and interpreting results in the context of the limitations.

Maternal health after Ebola: unmet needs and barriers to healthcare in rural Sierra Leone

Sierra Leone has the world's highest estimated maternal mortality. Following the 2014-16 Ebola outbreak, we described health outcomes and health-seeking behaviour amongst pregnant women to inform health policy. In October 2016-January 2017, we conducted a sequential mixed-methods study in urban and rural areas of Tonkolili District comprising: household survey targeting women who had given birth since onset of the Ebola outbreak; structured interviews at rural sites investigating maternal deaths and reporting; and in-depth interviews (IDIs) targeting mothers, community leaders and health workers. We selected 30 clusters in each area: by random GPS points (urban) and by random village selection stratified by population size (rural). We collected data on health-seeking behaviours, barriers to healthcare, childbirth and outcomes using structured questionnaires. IDIs exploring topics identified through the survey were conducted with a purposive sample and analysed thematically. We surveyed 608 women and conducted 29 structured and 72 IDIs. Barriers, including costs of healthcare and physical inaccessibility of healthcare facilities, delayed or prevented 90% [95% confidence interval (CI): 80-95] (rural) vs 59% (95% CI: 48-68) (urban) pregnant women from receiving healthcare. Despite a general preference for biomedical care, 48% of rural and 31% of urban women gave birth outside of a health facility; of those, just 4% and 34%, respectively received skilled assistance. Women expressed mistrust of healthcare workers (HCWs) primarily due to payment demanded for 'free' healthcare. HCWs described lack of pay and poor conditions precluding provision of quality care. Twenty percent of women reported labour complications. Twenty-eight percent of villages had materials to record maternal deaths. Pregnant women faced important barriers to care, particularly in rural areas, leading to high preventable mortality and morbidity. Women wanted to access healthcare, but services available were often costly, unreachable and poor quality. We recommend urgent interventions, including health promotion, free healthcare access and strengthening rural services to address barriers to maternal healthcare.

When it rains, it pours: detecting seasonal patterns in utilization of maternal healthcare in Mozambique using routine data

BACKGROUND

Climatic conditions and seasonal trends can affect population health, but typically, we consider the effect of climate on the epidemiology of communicable diseases. However, climate can also have an effect on access to care, particularly in remote rural areas of low- and middle-income countries. In this study, we investigate associations between the rainy season and the utilization of maternal health services in Mozambique.

METHODS

We examined patterns in the number of women receiving antenatal care (ANC) and delivering at a health facility for 2012-2019, using data from Mozambique's Health Management Information Systems. We investigated the association between seasonality (rainfall) and maternal health service utilization (ANC and institutional delivery) at national and provincial level. We fit a negative binomial regression model for institutional delivery and used it to estimate the yearly reduction in institutional deliveries due to the rainy season, with other factors held constant. We used the Lives Saved Tool (LiST) to model increases in mortality due to this estimated decrease in institutional delivery associated with the rainy season.

RESULTS

In our national analysis, the rate of ANC visits was 1% lower during the rainy season, adjusting for year and province (IRR = 0.99, 95% CI: 0.96-1.03). The rate of institutional deliveries was 6% lower during the rainy season than the dry season, after adjusting for time and province (IRR = 0.94, 95% CI: 0.92-0.96). In provincial analyses, all provinces except for Maputo-Cidade, Maputo-Province, Nampula, and Niassa showed a statistically significantly lower rate of institutional deliveries in the rainy season. None were statistically significantly lower for ANC. We estimate that, due to reductions in institutional delivery attributable only to the rainy season, there were 74 additional maternal deaths and 726 additional deaths of children under the age of 1 month in 2021, that would not have died if the mothers had instead delivered at a facility.

CONCLUSION

Fewer women deliver at a health facility during the rainy season in Mozambique than during the dry season. Barriers to receiving care during pregnancy and childbirth must be addressed using a multisectoral approach, considering the impact of geographical inequities.

The effects of changes in distance to nearest health facility on under-5 mortality and health care utilization in rural Malawi, 1980-1998

Background

Despite important progress, the burden of under-5 mortality remains unacceptably high, with an estimated 5.3 million deaths in 2018. Lack of access to health care is a major risk factor for under-5 mortality, and distance to health care facilities has been shown to be associated with less access to care in multiple contexts, but few such studies have used a counterfactual approach to produce causal estimates.

Methods

We combined retrospective reports on 18,714 births between 1980 and 1998 from the 2000 Malawi Demographic and Health Survey with a 1998 health facility census that includes the date of construction for each facility, including 335 maternity or maternity/dispensary facilities built in rural areas between 1980 and 1998. We estimated associations between distance to nearest health facility and (i) under-5 mortality, using Cox proportional hazards models, and (ii) maternal health care utilization (antenatal visits prior to delivery, place of delivery, receiving skilled assistance during delivery, and receiving a check-up following delivery), using linear probability models. We also estimated the causal effect of reducing the distance to nearest facility on those outcomes, using a two-way fixed effects approach.

Findings

We found that greater distance was associated with higher mortality (hazard ratio 1.007 for one additional kilometer [95%CI 1.001 to 1.014]) and lower health care utilization (for one additional kilometer: 1.2 percentage point (pp) increase in homebirth [95%CI 0.8 to 1.5]; 0.8 pp. decrease in at least three antenatal visits [95% CI − 1.4 to − 0.2]; 1.2 pp. decrease in skilled assistance during delivery [95%CI − 1.6 to − 0.8]). However, we found no effects of a decrease in distance to the nearest health facility on the hazard of death before age 5 years, nor on antenatal visits prior to delivery, place of delivery, or receiving skilled assistance during delivery. We also found that reductions in distance decrease the probability that a woman receives a check-up following delivery (2.4 pp. decrease for a 1 km decrease [95%CI 0.004 to 0.044]).

Conclusion

Reducing under-5 mortality and increasing utilization of care in rural Malawi and similar settings may require more than the construction of new health infrastructure. Importantly, the effects estimated here likely depend on the quality of health care, the availability of transportation, the demand for health services, and the underlying causes of mortality, among other factors.

Understanding adherence in virally suppressed and unsuppressed human immunodeficiency virus-positive urban patients on second-line antiretroviral treatment

Background

Understanding antiretroviral therapy (ART) adherence may assist in designing effective support interventions.

Objectives

This study elicited perspectives on how to promote treatment adherence from virologically suppressed and unsuppressed patients receiving second-line ART.

Methods

This was a cross-sectional study conducted with randomly selected patients active on second-line ART, from five public health facilities in the Johannesburg inner city. Data were collected on demographics, clinical information, participant’s experiences and ART knowledge. Virological failure was defined as exceeding 1000 copies/mL.

Results

The study sample comprised 149 participants; of which 47.7% (n = 71) were virally unsuppressed and 69.1% (n = 103) were women; the median age of the participants was 42 years (interquartile range [IQR] 36–47 years). Experiencing medication-related difficulties in taking second-line ART (p = 0.003), finding second-line regimen more difficult to take than a first-line regimen (p = 0.001) and experiencing side effects (p < 0.001) were all subjective predictors of virological failure. Participants’ recommendations for improving adherence included the introduction of a single tablet regimen (31.6%, n = 55), reducing the dosage to once daily (26.4%, n = 46) and reducing the pill size for second-line regimen (4.0%, n = 7).

Conclusion

The results of this study highlight the importance of improving patients’ knowledge about adherence and motivation to continue ART use despite the persistence of side effects and difficulties with taking medication.

Spatial access inequities and childhood immunisation uptake in Kenya

BACKGROUND

Poor access to immunisation services remains a major barrier to achieving equity and expanding vaccination coverage in many sub-Saharan African countries. In Kenya, the extent to which spatial access affects immunisation coverage is not well understood. The aim of this study was to quantify spatial accessibility to immunising health facilities and determine its influence on immunisation uptake in Kenya while controlling for potential confounders.

METHODS

Spatial databases of immunising facilities, road network, land use and elevation were used within a cost friction algorithim to estimate the travel time to immunising health facilities. Two travel scenarios were evaluated; (1) Walking only and (2) Optimistic scenario combining walking and motorized transport. Mean travel time to health facilities and proportions of the total population living within 1-h to the nearest immunising health facility were computed. Data from a nationally representative cross-sectional survey (KDHS 2014), was used to estimate the effect of mean travel time at survey cluster units for both fully immunised status and third dose of diphtheria-tetanus-pertussis (DPT3) vaccine using multi-level logistic regression models.

RESULTS

Nationally, the mean travel time to immunising health facilities was 63 and 40 min using the walking and the optimistic travel scenarios respectively. Seventy five percent of the total population were within one-hour of walking to an immunising health facility while 93% were within one-hour considering the optimistic scenario. There were substantial variations across the country with 62%(29/47) and 34%(16/47) of the counties with < 90% of the population within one-hour from an immunising health facility using scenarios 1 and 2 respectively. Travel times > 1-h were significantly associated with low immunisation coverage in the univariate analysis for both fully immunised status and DPT3 vaccine. Children living more than 2-h were significantly less likely to be fully immunised [AOR:0.56(0.33-0.94) and receive DPT3 [AOR:0.51(0.21-0.92) after controlling for household wealth, mother's highest education level, parity and urban/rural residence.

CONCLUSION

Travel time to immunising health facilities is a barrier to uptake of childhood vaccines in regions with suboptimal accessibility (> 2-h). Strategies that address access barriers in the hardest to reach communities are needed to enhance equitable access to immunisation services in Kenya.

Factors affecting mothers' intentions to visit healthcare facilities before hospitalisation of children with pneumonia in Biliran province, Philippines: a qualitative study

BACKGROUND AND OBJECTIVES

Despite a substantial reduction in the mortality rate of children under 5 years in the past 25 years, pneumonia remains the single-largest infectious cause of child deaths worldwide. This study explored the chronological order of visited healthcare facilities and practitioners, and the factors affecting mothers' intention to seek care before the hospitalisation of children with pneumonia.

METHODS AND ANALYSIS

A qualitative research design was employed using theory of planned behaviour as a framework for the analysis. Using purposive sampling technique, 11 mothers, whose children under 5 years old were hospitalised with severe pneumonia, were recruited for individual semi-structured interviews. Their socio-demographic information was analysed using descriptive statistics.

RESULTS

Mothers brought their sick children to multiple facilities, and 1 to 19 days had passed before hospitalisation. We identified four major factors determining mothers' intentions: (1) doing something useful for the sick child, (2) expecting the child to receive the necessary assessment and treatment, (3) accepting advice to visit a healthcare facility and be referred to a hospital and (4) considering issues and benefits associated with hospitalisation. Mothers noticed their children's unusual symptoms and monitored them while applying home remedies. They also took their children to traditional healers despite knowing that the treatments were not necessarily effective. Mothers expected children to be checked by health professionals and listened to advice from family members regarding the facilities to visit, and from healthcare staff to be referred to a hospital. Financial issues and the double burden of housework and caring for the hospitalised child were mothers' major concerns about hospitalisation.

CONCLUSION

Children were hospitalised after several days because they visited multiple healthcare facilities, including traditional healers. Improving care quality at healthcare facilities and reducing financial and mothers' burden may reduce the hospitalisation delay for children with pneumonia.

Measuring Accessibility of Healthcare Facilities for Populations with Multiple Transportation Modes Considering Residential Transportation Mode Choice

Accessibility research of healthcare facilities is developing towards multiple transportation modes (MTM), which are influenced by residential transportation choices and preferences. Due to differences in travel impact factors such as traffic conditions, origin location, distance to the destination, and economic cost, residents’ daily travel presents different residential transportation mode choices (RTMC). The purpose of our study was to measure the spatial accessibility of healthcare facilities based on MTM considering RTMC (MTM-RTMC). We selected the gravity two-step floating catchment area method (G2SFCA) as a fundamental model. Through the single transportation mode (STM), MTM, and MTM-RTMC, three aspects used to illustrate and redesign the G2SFCA, we obtained the MTM-RTMC G2SFCA model that integrates RTMC probabilities and the travel friction coefficient. We selected Nanjing as the experimental area, used route planning data of four modes (including driving, walking, public transportation, and bicycling) from a web mapping platform, and applied the three models to pediatric clinic services to measure accessibility. The results show that the MTM-RTMC mechanism is to make up for the traditional estimation of accessibility, which loses sight of the influence of residential transportation choices. The MTM-RTMC mechanism that provides a more realistic and reliable way can generalize to major accessibility models and offers preferable guidance for policymakers.

Distance sampling for epidemiology: an interactive tool for estimating under-reporting of cases from clinic data

BACKGROUND

Distance sampling methods are widely used in ecology to estimate and map the abundance of animal and plant populations from spatial survey data. The key underlying concept in distance sampling is the detection function, the probability of detecting the occurrence of an event as a function of its distance from the observer, as well as other covariates that may influence detection. In epidemiology, the burden and distribution of infectious disease is often inferred from cases that are reported at clinics and hospitals. In areas with few public health facilities and low accessibility, the probability of detecting a case is also a function of the distance between an infected person and the "observer" (e.g. a health centre). While the problem of distance-related under-reporting is acknowledged in public health; there are few quantitative methods for assessing and correcting for this bias when mapping disease incidence. Here, we develop a modified version of distance sampling for prediction of infectious disease incidence by relaxing some of the framework's fundamental assumptions. We illustrate the utility of this approach using as our example malaria distribution in rural Burkina Faso, where there is a large population at risk but relatively low accessibility of health facilities.

RESULTS

The modified distance-sampling framework was used to predict the probability of reporting malaria infection at 8 rural clinics, based on road-travel distances from villages. The rate at which reporting probability dropped with distance varied between clinics, depending on road and clinic positions. The probability of case detection was estimated as 0.3-1 in the immediate vicinity of the clinic, dropping to 0.1-0.6 at a travel distance of 10 km, and effectively zero at distances > 30-40 km.

CONCLUSIONS

To enhance the method's strategic impact, we provide an interactive mapping tool (as a self-contained R Shiny app) that can be used by non-specialists to interrogate model outputs and visualize how the overall probability of under-reporting and the catchment area of each clinic is influenced by changing the number and spatial allocation of health centres.

The Transport and Outcome of Sick Outborn Neonates Admitted to a Regional and District Hospital in the Upper West Region of Ghana: A Cross-Sectional Study

Optimum care of sick neonates often involves transporting them across different levels of care. Since their condition may deteriorate over time, attention needs to be paid to travel distances and how they are transferred. We examined the mode of transport, distances travelled, condition on arrival and outcome of outborn neonates admitted to a district and a regional hospital in Ghana using a cross-sectional study involving caregivers of neonates admitted to these hospitals. Information on referral characteristics and outcome were obtained from questionnaires and the child’s case notes. Overall, 153 caregivers and babies were studied. Twelve deaths, 7.8%, occurred. Neonates who died spent a median duration of 120 min at the first health facility they visited compared with 30 min spent by survivors; they travelled mostly by public buses, (41.7%), compared with 36.0% of survivors who used taxis. Majority of survivors, 70.2%, had normal heart rates on arrival compared with only 41.7% of neonates who died; hypothermia was present in 66.7% compared with 47.6% of survivors. These findings indicate that the logistics for neonatal transport were inadequate to keep the neonates stable during the transfer process, thus many of them were compromised especially those who died. Further studies are warranted.

Estimating hospital catchments from in-patient admission records: a spatial statistical approach applied to malaria

Admission records are seldom used in sub-Saharan Africa to delineate hospital catchments for the spatial description of hospitalised disease events. We set out to investigate spatial hospital accessibility for severe malarial anaemia (SMA) and cerebral malaria (CM). Malaria admissions for children between 1 month and 14 years old were identified from prospective clinical surveillance data recorded routinely at four referral hospitals covering two complete years between December 2015 to November 2016 and November 2017 to October 2018. These were linked to census enumeration areas (EAs) with an age-structured population. A novel mathematical-statistical framework that included EAs with zero observations was used to predict hospital catchment for malaria admissions adjusting for spatial distance. From 5766 malaria admissions, 5486 (95.14%) were linked to specific EA address, of which 272 (5%) were classified as cerebral malaria while 1001 (10%) were severe malaria anaemia. Further, results suggest a marked geographic catchment of malaria admission around the four sentinel hospitals although the extent varied. The relative rate-ratio of hospitalisation was highest at <1-hour travel time for SMA and CM although this was lower outside the predicted hospital catchments. Delineation of catchments is important for planning emergency care delivery and in the use of hospital data to define epidemiological disease burdens. Further hospital and community-based studies on treatment-seeking pathways to hospitals for severe disease would improve our understanding of catchments.

Travel time to health facilities in areas of outbreak potential: maps for guiding local preparedness and response

BACKGROUND

Repeated outbreaks of emerging pathogens underscore the need for preparedness plans to prevent, detect, and respond. As countries develop and improve National Action Plans for Health Security, addressing subnational variation in preparedness is increasingly important. One facet of preparedness and mitigating disease transmission is health facility accessibility, linking infected persons with health systems and vice versa. Where potential patients can access care, local facilities must ensure they can appropriately diagnose, treat, and contain disease spread to prevent secondary transmission; where patients cannot readily access facilities, alternate plans must be developed. Here, we use travel time to link facilities and populations at risk of viral hemorrhagic fevers (VHFs) and identify spatial variation in these respective preparedness demands.

METHODS AND FINDINGS

We used geospatial resources of travel friction, pathogen environmental suitability, and health facilities to determine facility accessibility of any at-risk location within a country. We considered in-country and cross-border movements of exposed populations and highlighted vulnerable populations where current facilities are inaccessible and new infrastructure would reduce travel times. We developed profiles for 43 African countries. Resulting maps demonstrate gaps in health facility accessibility and highlight facilities closest to areas at risk for VHF spillover. For instance, in the Central African Republic, we identified travel times of over 24 h to access a health facility. Some countries had more uniformly short travel times, such as Nigeria, although regional disparities exist. For some populations, including many in Botswana, access to areas at risk for VHF nationally was low but proximity to suitable spillover areas in bordering countries was high. Additional analyses provide insights for considering future resource allocation. We provide a contemporary use case for these analyses for the ongoing Ebola outbreak.

CONCLUSIONS

These maps demonstrate the use of geospatial analytics for subnational preparedness, identifying facilities close to at-risk populations for prioritizing readiness to detect, treat, and respond to cases and highlighting where gaps in health facility accessibility exist. We identified cross-border threats for VHF exposure and demonstrate an opportunity to improve preparedness activities through the use of precision public health methods and data-driven insights for resource allocation as part of a country's preparedness plans.

Clustering of Infant Mortality Within Families in Rural Burkina Faso

In this study, we analyze clustering of infant deaths within families living in a rural part of western Burkina Faso. The study included 9,220 infants, born between 1993 and 2009 in Nouna Health and Demographic Surveillance System (HDSS). A clustering of infant deaths in families was explored by calculating observed versus expected number of infant deaths within families for a given family size. In addition, risk ratios were calculated for infant death depending on the vital status of the previous sibling. We observed 470 infant deaths, yielding an overall infant mortality risk of 51/1,000 births. Clustering of infant deaths within families was observed (P = 0.004). In smaller families, the mortality of firstborns was higher than for the following siblings. The infant mortality risk was higher when the preceding sibling died in infancy (P = 0.03). The study supports the hypothesis of infant death clustering existing within rural families in West Africa. Further studies are needed to shed more light on these findings with the goal to develop effective interventions directed toward the families who already lost a child.

Impact of traffic variability on geographic accessibility to 24/7 emergency healthcare for the urban poor: A GIS study in Dhaka, Bangladesh

Ensuring access to healthcare in emergency health situations is a persistent concern for health system planners. Emergency services, including critical care units for severe burns and coronary events, are amongst those for which travel time is the most crucial, potentially making a difference between life and death. Although it is generally assumed that access to healthcare is not an issue in densely populated urban areas due to short distances, we prove otherwise by applying improved methods of assessing accessibility to emergency services by the urban poor that take traffic variability into account. Combining unique data on emergency health service locations, traffic flow variability and informal settlements boundaries, we generated time-cost based service areas to assess the extent to which emergency health services are reachable by urban slum dwellers when realistic traffic conditions and their variability in time are considered. Variability in traffic congestion is found to have significant impact on the measurement of timely access to, and availability of, healthcare services for slum populations. While under moderate traffic conditions all slums in Dhaka City are within 60-minutes travel time from an emergency service, in congested traffic conditions only 63% of the city's slum population is within 60-minutes reach of most emergency services, and only 32% are within 60-minutes reach of a Burn Unit. Moreover, under congested traffic conditions only 12% of slums in Dhaka City Corporation comply with Bangladesh's policy guidelines that call for access to 1 health service per 50,000 population for most emergency service types, and not a single slum achieved this target for Burn Units. Emergency Obstetric Care (EmOC) and First Aid & Casualty services provide the best coverage, with nearly 100% of the slum population having timely access within 60-minutes in any traffic condition. Ignoring variability in traffic conditions results in a 3-fold overestimation of geographic coverage and masks intra-urban inequities in accessibility to emergency care, by overestimating geographic accessibility in peripheral areas and underestimating the same for central city areas. The evidence provided can help policy makers and urban planners improve health service delivery for the urban poor. We recommend that taking traffic conditions be taken into account in future GIS-based analysis and planning for healthcare service accessibility in urban areas.

Who Stays and Who Goes: Predictors of Admission among Patients Presenting with Febrile Illness and a Positive Malaria Rapid Diagnostic Test in a Rural Ugandan Health Center

Not much is known about clinical decision-making in rural, low-resource settings regarding fever, a common reason for presentation to care. In this prospective cohort study of patients presenting with febrile illness to a rural Ugandan health center, we examined demographic and clinical factors predictive of an initial disposition of inpatient admission after clinical evaluation, but before laboratory testing. We then assessed the association of laboratory results and system factors with a change between initial and final disposition plans. Four thousand nine hundred twenty-four patients with suspected febrile illness were included in the primary analysis. The strongest predictors for an initial disposition of admission after clinical examination were impaired consciousness (adjusted risk ratio [aRR], 3.21; 95% confidence interval [CI]: 2.44-4.21) and fever on examination (aRR, 2.27; 95% CI: 1.79-2.87). Providers initially planned to discharge patients with significant vital sign abnormalities, including tachypnea (3.6%) and hypotension (1.3%). Anemia strongly predicted a final disposition of admission after an initial disposition of discharge (aRR, 48.34; 95% CI: 24.22-96.49); other laboratory abnormalities, including hypoglycemia and acidosis, did not change disposition planning. In those with an initial disposition of admission, living farther than the two neighboring villages was associated with a final disposition of discharge (aRR, 2.12; 95% CI: 1.10-4.12). A concerning number of patients with abnormal vital signs and laboratory results were not admitted for inpatient care. Geographic factors may influence a patient's final disposition contrary to a provider's initial disposition plan. Future work should assess longer term outcomes after discharge and a broader study population.

Service environment link and false discovery rate correction: Methodological considerations in population and health facility surveys

Background

Geospatial data are important in monitoring many aspects of healthcare development. Geographically linking health facility data with population data is an important area of public health research. Examining healthcare problems spatially and hierarchically assists with efficient resource allocation and the monitoring and evaluation of service efficacy at different levels. This paper explored methodological issues associated with geographic data linkage, and the spatial and multilevel analyses that could be considered in analysing maternal health service data.

Methods

The 2016 Ethiopia Demographic and Health Survey and the 2014 Ethiopia Service Provision Assessment data were used. Two geographic data linking methods were used to link these two datasets. Administrative boundary link was used to link a sample of health facilities data with population survey data for analysing three areas of maternal health service use. Euclidean buffer link was used for a census of hospitals to analyse caesarean delivery use in Ethiopia. The Global Moran’s I and the Getis-Ord Gi* statistics need to be carried out for identifying hot spots of maternal health service use in ArcGIS software. In addition to this, since the two datasets contain hierarchical data, a multilevel analysis was carried out to identify key determinants of maternal health service use in Ethiopia.

Results

Administrative boundary link gave more types of health facilities and more maternal health services as compared to the Euclidean buffer link. Administrative boundary link is the method of choice in case of sampled health facilities. However, for a census of health facilities, the Euclidean buffer link is the appropriate choice as this provides cluster level service environment estimates, which the administrative boundary link does not. Applying a False Discovery Rate correction enables the identification of true spatial clusters of maternal health service use.

Conclusions

A service environment link minimizes the methodological issues associated with geographic data linkage. A False Discovery Rate correction needs to be used to account for multiple and dependent testing while carrying out local spatial statistics. Examining maternal health service use both spatially and hierarchically has tremendous importance for identifying geographic areas that need special emphasis and for intervention purposes.

Geographic access to emergency obstetric services: a model incorporating patient bypassing using data from Mozambique

Introduction

Targeted approaches to further reduce maternal mortality require thorough understanding of the geographic barriers that women face when seeking care. Common measures of geographic access do not account for the time needed to reach services, despite substantial evidence that links proximity with greater use of facility services. Further, methods for measuring access often ignore the evidence that women frequently bypass close facilities based on perceptions of service quality. This paper aims to adapt existing approaches for measuring geographic access to better reflect women's bypassing behaviour, using data from Mozambique.

Methods

Using multiple data sources and modelling within a geographic information system, we calculated two segments of a patient's time to care: (1) home to the first preferred facility, assuming a woman might travel longer to reach a facility she perceived to be of higher quality; and (2) referral between the first preferred facility and facilities providing the highest level of care (eg, surgery). Combined, these two segments are total travel time to highest care. We then modelled the impact of expanding services and emergency referral infrastructure.

Results

The combination of upgrading geographically strategic facilities to provide the highest level of care and providing transportation to midlevel facilities modestly increased the percentage of the population with 2-hour access to the highest level of care (from 41% to 45%). The mean transfer time between facilities would be reduced by 39% (from 2.9 to 1.8 hours), and the mean total journey time by 18% (from 2.5 to 2.0 hours).

Conclusion

This adapted methodology is an effective tool for health planners at all levels of the health system, particularly to identify areas of very poor access. The modelled changes indicate substantial improvements in access and identify populations outside timely access for whom more innovative interventions are needed.

Achieving explanatory depth and spatial breadth in infectious disease modelling: Integrating active and passive case surveillance

Ideally, the data used for robust spatial prediction of disease distribution should be both high-resolution and spatially expansive. However, such in-depth and geographically broad data are rarely available in practice. Instead, researchers usually acquire either detailed epidemiological data with high resolution at a small number of active sampling sites, or more broad-ranging but less precise data from passive case surveillance. We propose a novel inferential framework, capable of simultaneously drawing insights from both passive and active data types. We developed a Bayesian latent point process approach, combining active data collection in a limited set of points, where in-depth covariates are measured, with passive case detection, where error-prone, large-scale disease data are accompanied only by coarse or remotely-sensed covariate layers. Using the example of malaria, we tested our method's efficiency under several hypothetical scenarios of reported incidence in different combinations of imperfect detection and spatial complexity of the environmental variables. We provide a simple solution to a widespread problem in spatial epidemiology, combining latent process modelling and spatially autoregressive modelling. By using active sampling and passive case detection in a complementary way, we achieved the best-of-both-worlds, in effect, a formal calibration of spatially extensive, error-prone data by localised, high-quality data.

The impacts of quantity and quality of health clinics on health behaviors and outcomes in Nigeria: analysis of health clinic census data

Background

Past studies have identified that inconvenient access to health clinics is one of the important barriers to health service utilization and health outcomes. However, establishing the link between the lack of access to health clinics and the high maternal and child morbidity and mortality in Nigeria has been a challenge due to the lack of data. This paper overcomes this problem by using the country’s health clinic census data.

Methods

Using the Nigerian health clinic census, we evaluate the intercorrelation between the quantity and the quality of health clinics available across the country. We also examine the correlation between the access to health clinics and health behaviors/outcomes for residents by merging the health clinic census data with data from the demographic and health survey (DHS). The health clinic census data makes it possible to capture the overall geographical allocation of health services across the country as well as their comprehensive relationship with health outcomes.

Results

We find a strong positive correlation between the quality of a health clinic and the quantity and quality of neighboring clinics. The high quality clinics are concentrated in areas where the density of clinics is high, and where more of the clinics around them are also of high quality. We also find that an increase in access to health clinics of high quality that are in close proximity is significantly and positively correlated with an improvement in health behaviors as well as health outcomes. Women who are more disadvantaged benefit more from the access to high quality clinics than others.

Conclusions

Health clinics of good quality are unevenly distributed geographically in Nigeria. The quality of health clinics should be of a level that can support the promotion of recommended health behaviors and achieve improved health outcomes throughout the country. Further studies are necessary to evaluate the optimal distribution of clinics of good quality, given that residents in less populated areas gain a higher marginal benefit from improved access to health service, despite the higher costs of supplying the service in those areas.

Health care utilization for common childhood illnesses in rural parts of Ethiopia: evidence from the 2016 Ethiopian demographic and health survey

Background

Generally, health care utilization in developing countries is low particularly rural community have lower health care utilization. Despite this fact, little is known about the magnitude and determinants of health care utilization for common childhood illnesses in Ethiopia. Thus, this study was conducted to determine the magnitude and to identify determinants of health care utilization for common childhood illnesses in the rural parts of Ethiopia.

Methods

For this study, data were obtained from the 2016 Ethiopian demographic and health survey. A total of 1576 mothers of under-five children were included in the analysis. Data analysis was performed using R software. Both univariable and multivariable logistic regression analysis were fitted to identify the determinants of health care utilization. Variables with a 95% confidence interval for odds ratio excluding one were considered as significant determinants of the outcome.

Results

The findings of this study revealed that only half (49.7%) (95%CI: 46.1–53.4%), 40.9% (95%CI 37.6–44.2%), and 38.0% (95%CI: 34.7–41.4%) of the children utilized health care for diarrhea, fever, and cough, respectively. Children age between 12 and 23 months (AOR: 1.58, 95%CI: 1.08–2.31), maternal education (AOR: 1.96, 95%CI: 1.34–2.88), and giving birth at health facilities (AOR: 1.49, 95%CI: 1.04–2.13) were found to be the determinants of health care utilization for diarrhea. Marital status (AOR: 0.25, 95%CI: 0.06–0.81), husbands’ education (AOR: 1.37, 95%CI: 1.01–1.86), and giving birth at health facilities (AOR: 1.51, 95%CI: 1.09–2.10) were factors significantly associated with health care utilization for fever. Children age between 12 and 23 months (AOR: 1.51, 95%CI: 1.03–2.22), maternal education (AOR: 1.70, 95%CI: 1.18–2.44), and giving birth at health facilities (AOR: 1.74, 95%CI: 1.23–2.46) were significantly associated with health care utilization for cough.

Conclusions

Low health care utilization for childhood illnesses was noticed. The health care utilization for diarrhea and cough was lower for children of ages between 0 and 11 months, mothers without formal education and home-delivered children’s. The health care utilization for fever was lower for separated parents, husbands without formal education, giving birth at home and from the poorest family. Programs to improve the educational status of a household are essential for better care utilization and children development.

Spatial distribution and determinants of asymptomatic malaria risk among children under 5 years in 24 districts in Burkina Faso

BACKGROUND

In malaria endemic countries, asymptomatic cases constitute an important reservoir of infections sustaining transmission. Estimating the burden of the asymptomatic population and identifying areas with elevated risk is important for malaria control in Burkina Faso. This study analysed the spatial distribution of asymptomatic malaria infection among children under 5 in 24 health districts in Burkina Faso and identified the determinants of this distribution.

METHODS

The data used in this study were collected in a baseline survey on "evaluation of the impact of pay for performance on the quality of care" conducted in 24 health districts in Burkina Faso, between October 2013 and March 2014. This survey involved 7844 households and 1387 community health workers. A Bayesian hierarchical logistic model that included spatial dependence and covariates was implemented to identify the determinants of asymptomatic malaria infection. The posterior probability distribution of a parameter from the model was summarized using odds ratio (OR) and 95% credible interval (95% CI).

RESULTS

The overall prevalence of asymptomatic malaria infection in children under 5 years of age was estimated at 38.2%. However, significant variation was observed between districts ranging from 11.1% in the district of Barsalgho to 77.8% in the district of Gaoua. Older children (48-59 vs < 6 months: OR: 6.79 [5.62, 8.22]), children from very poor households (Richest vs poorest: OR: 0.85 [0.74-0.96]), households located more than 5 km from a health facility (< 5 km vs  ≥ 5 km: OR: 1.14 [1.04-1.25]), in localities with inadequate number of nurses (< 3 vs  ≥ 3: 0.72 [0.62, 0.82], from rural areas (OR: 1.67 [1.39-2.01]) and those surveyed in high transmission period of asymptomatic malaria (OR: 1.27 [1.10-1.46]) were most at risk for asymptomatic malaria infection. In addition, the spatial analysis identified the following nine districts that reported significantly higher risks: Batié, Boromo, Dano, Diébougou, Gaoua, Ouahigouya, Ouargaye, Sapouy and Toma. The district of Zabré reported the lowest risk.

CONCLUSION

The analysis of spatial distribution of infectious reservoir allowed the identification of risk areas as well as the identification of individual and contextual factors. Such national spatial analysis should help to prioritize areas for increased malaria control activities.

Cross-border spatial accessibility of health care in the North-East Department of Haiti

BACKGROUND

The geographical accessibility of health services is an important issue especially in developing countries and even more for those sharing a border as for Haiti and the Dominican Republic. During the last 2 decades, numerous studies have explored the potential spatial access to health services within a whole country or metropolitan area. However, the impacts of the border on the access to health resources between two countries have been less explored. The aim of this paper is to measure the impact of the border on the accessibility to health services for Haitian people living close to the Haitian-Dominican border.

METHODS

To do this, the widely employed enhanced two-step floating catchment area (E2SFCA) method is applied. Four scenarios simulate different levels of openness of the border. Statistical analysis are conducted to assess the differences and variation in the E2SFCA results. A linear regression model is also used to predict the accessibility to health care services according to the mentioned scenarios.

RESULTS

The results show that the health professional-to-population accessibility ratio is higher for the Haitian side when the border is open than when it is closed, suggesting an important border impact on Haitians' access to health care resources. On the other hand, when the border is closed, the potential accessibility for health services is higher for the Dominicans.

CONCLUSION

The openness of the border has a great impact on the spatial accessibility to health care for the population living next to the border and those living nearby a road network in good conditions. Those findings therefore point to the need for effective and efficient trans-border cooperation between health authorities and health facilities. Future research is necessary to explore the determinants of cross-border health care and offers an insight on the spatial revealed access which could lead to a better understanding of the patients' behavior.

Home treatment and use of informal market of pharmaceutical drugs for the management of paediatric malaria in Cotonou, Benin

BACKGROUND

Malaria is the main cause of hospital admissions in Benin and a leading cause of death in childhood. Beside consultations, various studies have underlined the management of the disease through home treatment. The medicines used can be purchased in informal market of pharmaceutical drugs (IMPD) without prescription or any involvement of healthcare professional. Pharmaceutical drugs are sold by informal private vendors, who operate at any time in the immediate environment of the patients. The present study was conducted in Cotonou to study the health-seeking behaviour of caregivers to treat malaria in children under 12 years old. Factors associated with malaria home treatment and drugs purchase in IMPD were studied.

METHODS

A cross-sectional study was carried out among 340 children's caregivers who were interviewed about their socio-demographic characteristics and their care-seeking behaviour during the most recent episode of malaria in their children under 12. Medicines used and purchase place were also collected. Multivariate logistic regression model was used to determine factors associated with malaria home treatment and drug purchase in IMPD.

RESULTS

Beyond all the 340 caregivers, 116 (34%) consulted healthcare professional, 224 (66%) home treat the children, among whom 207 (61%) gave pharmaceutical drugs and 17 (5%) gave traditional remedies to children. Malaria home treatment was associated with family size, health insurance (OR = 0.396, 95% CI 0.169-0.928), and wealth quintiles where home treatment was less used by the richest (OR = 0.199, 95% CI 0.0676-0.522) compared to those in the poorest quintile. The caregivers age group 30-39 years was associated to the use of IMPD (OR = 0.383, 95% CI 0.152-0.964), the most economically wealthy people were less likely to use IMPD (wealth quintile richest: OR = 0.239, 95% CI 0.064-0.887; wealth quintile fourth OR = 0.271, 95% CI 0.100-0.735) compared to those in the poorest quintile. All caregivers who benefited from health insurance did not use IMPD.

CONCLUSION

This study highlights the link between worse economic conditions and accessibility to medical care as one of the main factors of malaria home treatment and drug purchase in IMPD, even if those two phenomena need to be understood apart.

Using geographical analysis to identify child health inequality in sub-Saharan Africa

One challenge to achieving Millennium Development Goals was inequitable access to quality health services. In order to achieve the Sustainable Development Goals, interventions need to reach underserved populations. Analyzing health indicators in small geographic units aids the identification of hotspots where coverage lags behind neighboring areas. The purpose of these analyses is to identify areas of low coverage or high need in order to inform effective resource allocation to reduce child health inequity between and within countries. Using data from The Demographic and Health Survey Program surveys conducted in 27 selected African countries between 2010 and 2014, we computed estimates for six child health indicators for subnational regions. We calculated Global Moran's I statistics and used Local Indicator of Spatial Association analysis to produce a spatial layer showing spatial associations. We created maps to visualize sub-national autocorrelation and spatial clusters. The Global Moran's I statistic was positive for each indicator (range: 0.41 to 0.68), and statistically significant (p <0.05), suggesting spatial autocorrelation across national borders, and highlighting the need to examine health indicators both across countries and within them. Patterns of substantial differences among contiguous subareas were apparent; the average intra-country difference for each indicator exceeded 20 percentage points. Clusters of cross-border associations were also apparent, facilitating the identification of hotspots and informing the allocation of resources to reduce child health inequity between and within countries. This study exposes differences in health indicators in contiguous geographic areas, indicating that specific regional and subnational, in addition to national, strategies to improve health and reduce health inequalities are warranted.