Geographic barriers to achieving universal health coverage: evidence from rural Madagascar

Unmet healthcare needs and the local extinction index: an analysis of regional disparities impacting South Korea's older adults

Background

This study examines the factors affecting unmet healthcare experiences by integrating individual-and community-level extinction indices.

Methods

Using spatial autocorrelation and multilevel modeling, the study utilizes data from the Community Health Survey and Statistics Korea for 218 local government regions from 2018 to 2019.

Results

The analysis identifies significant clustering, particularly in non-metropolitan regions with a higher local extinction index. At the individual level, some factors affect unmet medical needs, and unmet healthcare needs increase as the local extinction index at the community level increases.

Conclusion

The findings underscore the need for strategic efforts to enhance regional healthcare accessibility, particularly for vulnerable populations and local infrastructure development.

Problems accessing health care and under-5 mortality: a pooled analysis of 50 low- and middle-income countries

BACKGROUND

Access to health care remains suboptimal in low- and middle-income countries (LMICs) and continues to hinder survival in early childhood. We systematically assessed the association between problems accessing health care (PAHC) and under-five mortality (U5M).

METHODS

Child mortality data on 724 335 livebirths came from the latest Demographic and Health Surveys of 50 LMICs (2013-2021). Reasons for PAHC were classified into three domains: 'money needed for treatment' (economic), 'distance to health facility' (physical), 'getting permission' or 'not wanting to go alone' (socio-cultural). Multivariable logistic regression was used to estimate the association between PAHC (any and by each type) and U5M.

RESULTS

In our pooled sample, 47.3 children per 1000 livebirths died before age of 5, and 57.1% reported having experienced PAHC (ranging from 45.3% in Europe & Central Asia to 72.7% in Latin America & Caribbean). Children with any PAHC had higher odds of U5M (OR: 1.05, 95% CI: 1.02, 1.09), and this association was especially significant in sub-Saharan Africa. Of different domains of PAHC, socio-cultural PAHC was found to be most significant.

CONCLUSIONS

Access to health care in LMICs needs to be improved by expanding health care coverage, building health facilities, and focusing more on context-specific socio-cultural barriers.

Evaluation of a novel approach to community health care delivery in Ifanadiana District, Madagascar

Despite widespread adoption of community health (CH) systems, there are evidence gaps to support global best practice in remote settings where access to health care is limited and community health workers (CHWs) may be the only available providers. The nongovernmental health organization Pivot partnered with the Ministry of Public Health (MoPH) to pilot a new enhanced community health (ECH) model in rural Madagascar, where one CHW provided care at a stationary CH site while additional CHWs provided care via proactive household visits. The program included professionalization of the CHW workforce (i.e., targeted recruitment, extended training, financial compensation) and twice monthly supervision of CHWs. For the first eighteen months of implementation (October 2019-March 2021), we compared utilization and proxy measures of quality of care in the intervention commune (local administrative unit) and five comparison communes with strengthened community health programs under a different model. This allowed for a quasi-experimental study design of the impact of ECH on health outcomes using routinely collected programmatic data. Despite the substantial support provided to other CHWs, the results show statistically significant improvements in nearly every indicator. Sick child visits increased by more than 269.0% in the intervention following ECH implementation. Average per capita monthly under-five visits were 0.25 in the intervention commune and 0.19 in the comparison communes (p<0.01). In the intervention commune, 40.3% of visits were completed at the household via proactive care. CHWs completed all steps of the iCCM protocol in 85.4% of observed visits in the intervention commune (vs 57.7% in the comparison communes, p-value<0.01). This evaluation demonstrates that ECH can improve care access and the quality of service delivery in a rural health district. Further research is needed to assess the generalizability of results and the feasibility of national scale-up as the MoPH continues to define the national community health program.

Applying a zero-corrected, gravity model estimator reduces bias due to heterogeneity in healthcare utilization in community-scale, passive surveillance datasets of endemic diseases

Data on population health are vital to evidence-based decision making but are rarely adequately localized or updated in continuous time. They also suffer from low ascertainment rates, particularly in rural areas where barriers to healthcare can cause infrequent touch points with the health system. Here, we demonstrate a novel statistical method to estimate the incidence of endemic diseases at the community level from passive surveillance data collected at primary health centers. The zero-corrected, gravity-model (ZERO-G) estimator explicitly models sampling intensity as a function of health facility characteristics and statistically accounts for extremely low rates of ascertainment. The result is a standardized, real-time estimate of disease incidence at a spatial resolution nearly ten times finer than typically reported by facility-based passive surveillance systems. We assessed the robustness of this method by applying it to a case study of field-collected malaria incidence rates from a rural health district in southeastern Madagascar. The ZERO-G estimator decreased geographic and financial bias in the dataset by over 90% and doubled the agreement rate between spatial patterns in malaria incidence and incidence estimates derived from prevalence surveys. The ZERO-G estimator is a promising method for adjusting passive surveillance data of common, endemic diseases, increasing the availability of continuously updated, high quality surveillance datasets at the community scale.

A multilevel analysis of social determinants of skilled birth attendant utilisation among married and cohabiting women of Madagascar

BACKGROUND

Maternal mortality ratio (MMR) in Madagascar is 392 deaths per 100 000 live births, and this is a major public health concern. One of the strategies for reducing MMR and achieving target 3.1 of the Sustainable Development Goals (i.e. reducing the global MMR below 70 per 100 000 live births) is the utilisation of skilled birth attendants (SBAs). This analysis examined the prevalence and social determinants of SBA utilisation among married and cohabiting women of Madagascar.

METHODS

Data from the 2021 Madagascar Demographic and Health Surveys was analysed on a weighted sample of 6997 married and cohabiting women. A multilevel regression was carried out to determine the social determinants of utilising SBAs. The results are presented as odds ratios (ORs) associated with 95% confidence intervals (CIs) and a p-value <0.05 to determine the significant associations.

RESULTS

The prevalence of SBAs among married and cohabiting women of Madagascar was 64.4% (95% CI 0.62 to 0.68). In model 3 of the multilevel regression, women 35-39 y of age (adjusted OR [aOR] 1.86 [95% CI 1.30 to 2.60]), women with secondary/higher education (aOR 1.67 [95% CI 1.32 to 2.10]), women whose partners had secondary/higher education (aOR 1.58 [95% CI 1.25 to 1.99]), cohabiting women (aOR 1.33 [95% CI 1.07 to 1.65]), women who had four or more antenatal care visits (aOR  2.05 [95% CI 1.79 to 2.35]), female household head (aOR 1.44 [95% CI 1.06 to 1.95]), Muslims (aOR 1.58 [95% CI 0.71 to 3.53]), those of the richest wealth index (aOR 4.32 [95% CI 2.93 to 6.36]) and women who lived in communities with high literacy levels (aOR 2.17 [95% CI 1.57 to 3.00]) had higher odds of utilisation of SBA.

CONCLUSION

This current analysis revealed low SBA utilisation among married and cohabiting women in Madagascar. The analysis points to the fact that understaffing and inaccessibility of health facilities remain major contributors to the low utilisation of SBAs. The findings call on the government and stakeholders in Madagascar to consider implementing programs that will empower women and focus on disadvantaged groups. These programs could include providing free maternal healthcare services to all pregnant women and intensifying health education programs that target women and their partners with no formal education.

Using drivers and transmission pathways to identify SARS-like coronavirus spillover risk hotspots

The emergence of SARS-like coronaviruses is a multi-stage process from wildlife reservoirs to people. Here we characterize multiple drivers-landscape change, host distribution, and human exposure-associated with the risk of spillover of zoonotic SARS-like coronaviruses to help inform surveillance and mitigation activities. We consider direct and indirect transmission pathways by modeling four scenarios with livestock and mammalian wildlife as potential and known reservoirs before examining how access to healthcare varies within clusters and scenarios. We found 19 clusters with differing risk factor contributions within a single country (N = 9) or transboundary (N = 10). High-risk areas were mainly closer (11-20%) rather than far ( < 1%) from healthcare. Areas far from healthcare reveal healthcare access inequalities, especially Scenario 3, which includes wild mammals and not livestock as secondary hosts. China (N = 2) and Indonesia (N = 1) had clusters with the highest risk. Our findings can help stakeholders in land use planning, integrating healthcare implementation and One Health actions.

Drivers of informal sector and non-prescription medication use in pediatric populations in a low- and middle-income setting: A prospective cohort study in Zambia

Obtaining medication from the informal sector is common in low- and middle- income countries. Informal sector use increases the risk for inappropriate medication use, including inappropriate antibiotic usage. Infants are at the highest risk of complications from inappropriate medication use, yet there is insufficient knowledge about the risk factors driving caregivers to obtain medication from the informal sector for young children. We aimed to define infant and illness characteristics associated with use of medication purchased in the informal sector for infants up to fifteen months of age in Zambia. We used data from, a prospective cohort study (ROTA-biotic) conducted among 6 weeks to 15 months old children in Zambia, which is nested within an ongoing phase III rotavirus vaccine trial (Clinicaltrial.gov NCT04010448). Weekly in-person surveys collected information about illness episodes and medication usage for the trial population and for a community control cohort. The primary outcome for this study was whether medication was purchased in the formal sector (hospital or clinic) or informal sector (pharmacy, street vendor, friend/relative/neighbor, or chemical shop) per illness episode. Descriptive analyses were used to describe the study population, and the independent and medication use variables stratified by the outcome. A mixed-effects logistic regression model with a participant-level random intercept was used to identify independent variables associated with the outcome. The analysis included 439 participants accounting for 1927 illness episodes over fourteen months in time. Medication was purchased in the informal sector for 386 (20.0%) illness episodes, and in the formal sector for 1541 (80.0%) illness episodes. Antibiotic usage was less common in the informal sector than in the formal sector (29.3% vs 56.2%, p < 0.001, chi-square). Most medications purchased in the informal sector were orally administered (93.4%), and non-prescribed (78.8%). Increased distance from the closest study site (OR: 1.09; 95% CI: 1.01, 1.17), being included in the community cohort site (OR: 3.18; 95% CI: 1.86, 5.46), illnesses with general malaise fever, or headache (OR: 2.62; 95% CI: 1.75, 3.93), and wound/skin disease (OR: 0.36; 95% CI: 0.18, 0.73) were associated with use of medication from the informal sector. Sex, socioeconomic status, and gastrointestinal disease were not associated with use of medication from the informal sector. Informal sector medication use is common and, in this study, risk factors for obtaining medications in the informal sector included a long distance to a formal clinic, type of illness, and not being enrolled in a clinical trial. Continued research on medication use from the informal sector is crucial and should include generalizable study populations, information on severity of disease, emphasis on qualitative research, and a move towards testing interventions that aim to improve access to formal health care settings. Our findings suggest that improved access to formal health care services may decrease reliance on medication from the informal sector for infants.

Predicting health services utilization using a score of perceived barriers to medical care: evidence from rural Senegal

BACKGROUND

Ensuring access to healthcare services is a key element to achieving the Sustainable Development Goal 3 of "promoting healthy lives and well-being for all" through Universal Health Coverage (UHC). However, in the context of low- and middle-income countries, most studies focused on financial protection measured through catastrophic health expenditures (CHE), or on health services utilization among specific populations exhibiting health needs (such as pregnancy or recent sickness).

METHODS

This study aims at building an individual score of perceived barriers to medical care (PBMC) in order to predict primary care utilization (or non-utilization). We estimate the score on six items: (1) knowing where to go, (2) getting permission, (3) having money, (4) distance to the facility, (5) finding transport, and (6) not wanting to go alone, using individual data from 1787 adult participants living in rural Senegal. We build the score via a stepwise descendent explanatory factor analysis (EFA), and assess its internal consistency. Finally, we assess the construct validity of the factor-based score by testing its association (univariate regressions) with a wide range of variables on determinants of healthcare-seeking, and evaluate its predictive validity for primary care utilization.

RESULTS

EFA yields a one-dimensional score combining four items with a 0.7 Cronbach's alpha indicating good internal consistency. The score is strongly associated-p-values significant at the 5% level-with determinants of healthcare-seeking (including, but not limited to, sex, education, marital status, poverty, and distance to the health facility). Additionally, the score can predict non-utilization of primary care at the household level, utilization and non-utilization of primary care following an individual's episode of illness, and utilization of primary care during pregnancy and birth. These results are robust to the use of a different dataset.

CONCLUSION

As a valid, sensitive, and easily documented individual-level indicator, the PBMC score can be a complement to regional or national level health services coverage to measure health services access and predict utilization. At the individual or household level, the PBMC score can also be combined with conventional metrics of financial risk protection such as CHE to comprehensively document deficits in, and progress towards UHC.

Predictors for achieving adequate antenatal care visits during pregnancy: a cross-sectional study in rural Northwest Rwanda

BACKGROUND

Inadequate antenatal care (ANC) in low-income countries has been identified as a risk factor for poor pregnancy outcome. While many countries, including Rwanda, have near universal ANC coverage, a significant proportion of pregnant women do not achieve the recommended regimen of four ANC visits. The present study aimed to explore the factors associated with achieving the recommendation, with an emphasis on the distance from household to health facilities.

METHODS

A geo-referenced cross-sectional study was conducted in Rutsiro district, Western province of Rwanda with 360 randomly selected women. Multiple logistic regression analysis including adjusted odd ratio (aOR) were performed to identify factors associated with achieving the recommended four ANC visits.

RESULTS

The majority (65.3%) of women had less than four ANC visits during pregnancy. We found a significant and negative association between distance from household to health facility and achieving the recommended four ANC visits. As the distance increased by 1 km, the odds of achieving the four ANC visits decreased by 19% (aOR = 0.81, P = 0.024). The odds of achieving the recommended four ANC visits were nearly two times higher among mothers with secondary education compared with mothers with primary education or less (aOR = 1.90, P = 0.038). In addition, mothers who responded that their household members always seek health care when necessary had 1.7 times higher odds of achieving four ANC visits compared with those who responded as unable to seek health care (aOR = 1.7, P = 0.041). Furthermore, mothers from poor households had 2.1 times lower odds of achieving four ANC visits than mothers from slightly better-off households (aOR = 2.1, P = 0.028).

CONCLUSIONS

Findings from the present study suggest that, in Rutsiro district, travel distance to health facility, coupled with socio-economic constraints, including low education and poverty can make it difficult for pregnant women to achieve the recommended ANC regimen. Innovative strategies are needed to decrease distance by bringing ANC services closer to pregnant women and to enhance ANC seeking behaviour. Interventions should also focus on supporting women to attain at least secondary education level as well as to improve the household socioeconomic status of pregnant women, with a particular focus on women from poor households.

Climatic, land-use and socio-economic factors can predict malaria dynamics at fine spatial scales relevant to local health actors: Evidence from rural Madagascar

While much progress has been achieved over the last decades, malaria surveillance and control remain a challenge in countries with limited health care access and resources. High-resolution predictions of malaria incidence using routine surveillance data could represent a powerful tool to health practitioners by targeting malaria control activities where and when they are most needed. Here, we investigate the predictors of spatio-temporal malaria dynamics in rural Madagascar, estimated from facility-based passive surveillance data. Specifically, this study integrates climate, land-use, and representative household survey data to explain and predict malaria dynamics at a high spatial resolution (i.e., by Fokontany, a cluster of villages) relevant to health care practitioners. Combining generalized linear mixed models (GLMM) and path analyses, we found that socio-economic, land use and climatic variables are all important predictors of monthly malaria incidence at fine spatial scales, via both direct and indirect effects. In addition, out-of-sample predictions from our model were able to identify 58% of the Fokontany in the top quintile for malaria incidence and account for 77% of the variation in the Fokontany incidence rank. These results suggest that it is possible to build a predictive framework using environmental and social predictors that can be complementary to standard surveillance systems and help inform control strategies by field actors at local scales.

Identification of factors associated with residual malaria transmission using school-based serological surveys in settings pursuing elimination

Background

Targeted research on residual malaria transmission is important to improve strategies in settings pursuing elimination, where transmission reductions prove challenging. This study aimed to detect and characterize spatial heterogeneity and factors associated with Plasmodium falciparum infections and exposure, P. falciparum apical membrane antigen 1 (PfAMA1) antibody (Ab) response, in the Central Highlands of Madagascar (CHL).

Methods

From May to July 2014, a cross-sectional school-based survey was carried out in 182 fokontany (villages) within 7 health districts of the CHL. Rapid diagnostic tests (RDTs) and a bead-based immunoassay including PfAMA1 antigen biomarker were used to estimate malaria prevalence and seroprevalence, respectively. Local Moran’s I index was used to detect spatial “hotspots”. Remotely sensed environmental data—temperature, vegetation indices, land covers, and elevation—were used in multivariable mixed-effects logistic regression models to characterize factors associated with malaria infection and cumulative exposure.

Results

Among 6,293 school-children ages 2–14 years surveyed, RDT prevalence was low at 0.8% (95% CI 0.6–1.1%), while PfAMA1 Ab seroprevalence was 7.0% (95% CI 6.4–7.7%). Hotspots of PfAMA1 Ab seroprevalence were observed in two districts (Ankazobe and Mandoto). Seroprevalence increased for children living > 5 km from a health centre (adjusted odds ratio (OR) = 1.6, 95% CI 1.2–2.2), and for those experiencing a fever episode in the previous 2 weeks (OR 1.7, 95% CI 1.2–2.4), but decreased at higher elevation (for each 100-m increase, OR = 0.7, 95% CI 0.6–0.8). A clear age pattern was observed whereby children 9–10 years old had an OR of 1.8 (95% CI 1.2–2.4), children 11–12 years an OR of 3.7 (95% CI 2.8–5.0), and children 13–14 years an OR of 5.7 (95% CI 4.0–8.0) for seropositivity, compared with younger children (2–8 years).

Conclusion

The use of serology in this study provided a better understanding of malaria hotspots and associated factors, revealing a pattern of higher transmission linked to geographical barriers in health care access. The integration of antibody-assays into existing surveillance activities could improve exposure assessment, and may help to monitor the effectiveness of malaria control efforts and adapt elimination interventions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-022-04260-0.

Rural Transportation Infrastructure in Low- and Middle-Income Countries: A Review of Impacts, Implications, and Interventions

The rural transport infrastructure sector is a critical force for sustainable development that is interwoven with many other sectors. Rural transportation is an underlying driver of many of the Sustainable Development Goals (SDGs) and a crucial contributor to many socioeconomic benefits for rural people around the world. This review paper expands upon, enhances, and cross-references the perspectives outlined in previous rural infrastructure-focused review papers. Firstly, this work gives a thorough look into the progress of the rural transportation sector in recent years by focusing on the thematic relationships between infrastructure and other components of sustainable development, namely, economics and agriculture, policy and governance, health, gender, education, and climate change and the environment. Secondly, several strategies, approaches, and tools employed by governments and practitioners within the rural transport sector are analyzed and discussed for their contributions to the wellbeing of rural dwellers in low- and middle-income countries (LMICs). These include rural roads, bridges, maintenance, and non-infrastructural approaches that include concepts such as advanced technological innovations, intermediate modes of transport (IMTs), and transport services. This paper concludes that enhancement, improvement, and extension of rural transportation infrastructure brings significant benefits to rural dwellers. However, this paper also calls for additional integration of the sector and increased usage of systems approaches that view rural transport as an active part of many other sectors and a key leverage point within rural development as a whole. Further, this paper notes areas for future research and investigation, including increased investigation of the relationship between rural transportation infrastructure and education, improved data collection and management in support of improved policymaking, improved prioritization of interventions and institutionalization of maintenance, and expansion of pro-poor transportation strategies and interventions.

Geographic barriers to care persist at the community healthcare level: Evidence from rural Madagascar

Geographic distance is a critical barrier to healthcare access, particularly for rural communities with poor transportation infrastructure who rely on non-motorized transportation. There is broad consensus on the importance of community health workers (CHWs) to reduce the effects of geographic isolation on healthcare access. Due to a lack of fine-scale spatial data and individual patient records, little is known about the precise effects of CHWs on removing geographic barriers at this level of the healthcare system. Relying on a high-quality, crowd-sourced dataset that includes all paths and buildings in the area, we explored the impact of geographic distance from CHWs on the use of CHW services for children under 5 years in the rural district of Ifanadiana, southeastern Madagascar from 2018-2021. We then used this analysis to determine key features of an optimal geographic design of the CHW system, specifically optimizing a single CHW location or installing additional CHW sites. We found that consultation rates by CHWs decreased with increasing distance patients travel to the CHW by approximately 28.1% per km. The optimization exercise revealed that the majority of CHW sites (50/80) were already in an optimal location or shared an optimal location with a primary health clinic. Relocating the remaining CHW sites based on a geographic optimum was predicted to increase consultation rates by only 7.4%. On the other hand, adding a second CHW site was predicted to increase consultation rates by 31.5%, with a larger effect in more geographically dispersed catchments. Geographic distance remains a barrier at the level of the CHW, but optimizing CHW site location based on geography alone will not result in large gains in consultation rates. Rather, alternative strategies, such as the creation of additional CHW sites or the implementation of proactive care, should be considered.