Treatment-seeking behaviour in low- and middle-income countries estimated using a Bayesian model

Willingness to accept and participate in a Microsporidia MB-based mosquito release strategy: a community-based rapid assessment in western Kenya

BACKGROUND

Microsporidia MB, an endosymbiont naturally found in Anopheles mosquitoes inhibits transmission of Plasmodium and is a promising candidate for a transmission-blocking strategy that may involve mosquito release. A rapid assessment was carried out to develop insight into sociodemographic factors, public health concerns, and malaria awareness, management, and prevention practices with the willingness to accept and participate in Microsporidia MB-based transmission-blocking strategy to develop an informed stakeholder engagement process.

METHODS

The assessment consisted of a survey conducted in two communities in western Kenya that involved administering a questionnaire consisting of structured, semi-structured, and open questions to 8108 household heads.

RESULTS

There was an overall high level of willingness to accept (81%) and participate in the implementation of the strategy (96%). Although the willingness to accept was similar in both communities, Ombeyi community was more willing to participate (OR 22, 95% CI 13-36). Women were less willing to accept (OR 0.8, 95% CI 0.7-0.9) compared to men due to fear of increased mosquito bites near homes. Household heads with incomplete primary education were more willing to accept (OR 1.6, 95% CI 01.2-2.2) compared to those educated to primary level or higher. Perceiving malaria as a moderate or low public health issue was also associated with a lower willingness to accept and participate. Experience of > 3 malaria cases in the family over the last six months and knowledge that malaria is transmitted by only mosquito bites, increased the willingness to accept but reduced the willingness to participate. Awareness of malaria control methods based on mosquitoes that cannot transmit malaria increases the willingness to participate.

CONCLUSION

The study showed a high level of willingness to accept and participate in a Microsporidia MB-based strategy in the community, which is influenced by several factors such as community, disease risk perception, gender, education level, knowledge, and experience of malaria. Further research will need to focus on understanding the concerns of women, educated, and employed community members, and factors that contribute to the lower disease risk perception. This improved understanding will lead to the development of an effective communication strategy.

Health information sources and health-seeking behaviours of Filipinos living in medically underserved communities: Empirical quantitative research

AIMS

To describe sources of health information and health-seeking behaviours of adults (aged ≥18) living in medically underserved communities in the Philippines.

DESIGN

This is a secondary, quantitative analysis from a cross-sectional parent study. Participants completed a 10-item, self-report survey on their sources of health information, healthcare providers sought for health and wellness and health-seeking behaviours when ill. Responses were evaluated across two age groups (<60 vs. ≥60 years) and genders using generalized linear mixed models.

RESULTS

Surveys were completed by 1202 participants in rural settings (64.6% female, mean age 49.5 ± 17.6). Friends and/or family were their key source of health information (59.6%), followed by traditional media (37%) and healthcare professionals (12.2%). For health promotion, participants went to healthcare professionals (60.9%), informal healthcare providers (17.2%) or others (7.2%). When ill, they visited a healthcare professional 69.1% of the time, self-medicated (43.9%), prayed (39.5%) or sought treatment from a rural health clinic (31.5%). We also found differences in health-seeking behaviours based on age and gender.

CONCLUSIONS

Our findings highlight the need to organize programs that explicitly deliver accurate health information and adequate care for wellness and illness. Study findings emphasize the importance of integrating family, friends, media and healthcare professionals, including public health nurses, to deliver evidence-based health information, health promotion and sufficient treatment to medically underserved Filipinos.

IMPLICATIONS

New knowledge provides valuable information to healthcare providers, including public health nurses, in addressing health disparities among medically underserved Filipinos.

IMPACT

This study addresses the current knowledge gap in a medically vulnerable population. Healthcare professionals are not the primary sources of health information. Approximately one-third of participants do not seek them for health promotion or treatment even when ill, exacerbating health inequities. More work is necessary to support initiatives in low- and middle-income countries such as the Philippines to reduce health disparities.

REPORTING METHOD

We adhered to the reporting guidelines of STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) for cross-sectional studies.

PATIENT OR PUBLIC CONTRIBUTION

There was no patient or public contribution as our study design and methodology do not make this necessary.

An Estimate Of The Return On Investment Of A Malaria Vaccine In 20 Sub-Saharan African Countries, 2021-30

Malaria is a leading global health problem that was responsible for an estimated 619,000 deaths worldwide in 2021. We modeled the return on investment (ROI) for the introduction and continuation of a four-dose malaria vaccine, RTS,S/AS01, from 2021 to 2030 in twenty sub-Saharan African countries supported by Gavi, the Vaccine Alliance. We used the Decade of Vaccine Economics benefits and costing outputs to calculate an ROI using health impact data modeled by the Swiss Tropical and Public Health Institute (hereafter "Swiss") and Imperial College London (hereafter "Imperial"). The Swiss estimates with a base vaccine price of US$7.00 resulted in an ROI of 0.42, and the Imperial impact estimates with the same base vaccine price resulted in an ROI of 2.30. Inclusion of the fifth seasonal dose for ten countries exhibiting high seasonal disease burden increased the Swiss ROI by 143 percent, to 1.02, and the Imperial ROI by 23.5 percent, to 2.84. To improve ROI, decision makers should continue to improve delivery platforms, decrease vaccine delivery costs, deliver the malaria vaccine in fewer doses, and provide access to vaccine resources.

Travel scenario workshops for geographical accessibility modeling of health services: A transdisciplinary evaluation study

Introduction

Limited geographical access to quality Emergency Obstetric and Newborn Care (EmONC) is a major driver of high maternal mortality. Geographic access to EmONC facilities is identified by the global community as a critical issue for reducing maternal mortality and is proposed as a global indicator by the Ending Preventable Maternal Mortality (EPMM) initiative. Geographic accessibility models can provide insight into the population that lacks adequate access and on the optimal distribution of facilities and resources. Travel scenarios (i.e., modes and speed of transport) used to compute geographical access to healthcare are a key input to these models and should approximate reality as much as possible. This study explores strategies to optimize and harmonize knowledge elicitation practices for developing travel scenarios.

Methods

Knowledge elicitation practices for travel scenario workshops (TSW) were studied in 14 African and South-Asian countries where the United Nations Population Fund supported ministries of health and governments in strengthening networks of EmONC facilities. This was done through a mixed methods evaluation study following a transdisciplinary approach, applying the four phases of the Interactive Learning and Action methodology: exploration, in-depth, integration, and prioritization and action planning. Data was collected in November 2020-June 2021 and involved scoping activities, stakeholder identification, semi-structured interviews (N = 9), an evaluation survey (N = 31), and two co-creating focus group discussions (N = 8).

Results

Estimating realistic travel speeds and limited time for the workshop were considered as the largest barriers. The identified opportunities were inclusively prioritized, whereby preparation; a favorable composition of attendees; validation practices; and evaluation were anticipated to be the most promising improvement strategies, explaining their central place on the co-developed initial standard operating procedure (SOP) for future TSWs. Mostly extensive preparation-both on the side of the organization and the attendees-was anticipated to address nearly all of the identified TSW challenges.

Conclusion

This study showed that the different identified stakeholders had contradicting, complementing and overlapping ideas about strategies to optimize and harmonize TSWs. Yet, an initial SOP was inclusively developed, emphasizing practices for before, during and after each TSW. This SOP is not only relevant in the context of the UNFPA EmONC development approach, but also for monitoring the newly launched EPMM indicator and even in the broader field of geographic accessibility modeling.

National-scale simulation of human movement in a spatially coupled individual-based model of malaria in Burkina Faso

Malaria due to the Plasmodium falciparum parasite remains a threat to human health despite eradication efforts and the development of anti-malarial treatments, such as artemisinin combination therapies. Human movement and migration have been linked to the propagation of malaria on national scales, highlighting the need for the incorporation of human movement in modeling efforts. Spatially couped individual-based models have been used to study how anti-malarial resistance evolves and spreads in response to drug policy changes; however, as the spatial scale of the model increases, the challenges associated with modeling of movement also increase. In this paper we discuss the development, calibration, and validation of a movement model in the context of a national-scale, spatial, individual-based model used to study the evolution of drug resistance in the malaria parasite.

Mapping the endemicity and seasonality of clinical malaria for intervention targeting in Haiti using routine case data

Towards the goal of malaria elimination on Hispaniola, the National Malaria Control Program of Haiti and its international partner organisations are conducting a campaign of interventions targeted to high-risk communities prioritised through evidence-based planning. Here we present a key piece of this planning: an up-to-date, fine-scale endemicity map and seasonality profile for Haiti informed by monthly case counts from 771 health facilities reporting from across the country throughout the 6-year period from January 2014 to December 2019. To this end, a novel hierarchical Bayesian modelling framework was developed in which a latent, pixel-level incidence surface with spatio-temporal innovations is linked to the observed case data via a flexible catchment sub-model designed to account for the absence of data on case household locations. These maps have focussed the delivery of indoor residual spraying and focal mass drug administration in the Grand’Anse Department in South-Western Haiti.

How geographic access to care shapes disease burden: The current impact of post-exposure prophylaxis and potential for expanded access to prevent human rabies deaths in Madagascar

Background

Post-exposure prophylaxis (PEP) is highly effective at preventing human rabies deaths, however access to PEP is limited in many rabies endemic countries. The 2018 decision by Gavi to add human rabies vaccine to its investment portfolio should expand PEP availability and reduce rabies deaths. We explore how geographic access to PEP impacts the rabies burden in Madagascar and the potential benefits of improved provisioning.

Methodology & principal findings

We use spatially resolved data on numbers of bite patients seeking PEP across Madagascar and estimates of travel times to the closest clinic providing PEP (N = 31) in a Bayesian regression framework to estimate how geographic access predicts reported bite incidence. We find that travel times strongly predict reported bite incidence across the country. Using resulting estimates in an adapted decision tree, we extrapolate rabies deaths and reporting and find that geographic access to PEP shapes burden sub-nationally. We estimate 960 human rabies deaths annually (95% Prediction Intervals (PI): 790–1120), with PEP averting an additional 800 deaths (95% PI: 640–970) each year. Under these assumptions, we find that expanding PEP to one clinic per district (83 additional clinics) could reduce deaths by 19%, but even with all major primary clinics provisioning PEP (1733 additional clinics), we still expect substantial rabies mortality. Our quantitative estimates are most sensitive to assumptions of underlying rabies exposure incidence, but qualitative patterns of the impacts of travel times and expanded PEP access are robust.

Conclusions & significance

PEP is effective at preventing rabies deaths, and in the absence of strong surveillance, targeting underserved populations may be the most equitable way to provision PEP. Given the potential for countries to use Gavi funding to expand access to PEP in the coming years, this framework could be used as a first step to guide expansion and improve targeting of interventions in similar endemic settings where PEP access is geographically restricted and baseline data on rabies risk is lacking. While better PEP access should save many lives, improved outreach, surveillance, and dog vaccination will be necessary, and if rolled out with Gavi investment, could catalyze progress towards achieving zero rabies deaths.

Canine rabies causes an estimated 60,000 deaths each year across the world, primarily in low- and middle-income countries where people have limited access to both human vaccines (post-exposure prophylaxis or PEP) and dog rabies vaccines. Given that we have the tools to prevent rabies deaths, a global target has been set to eliminate deaths due to canine rabies by 2030, and recently, Gavi, a multilateral organization that aims to improve access to vaccines in the poorest countries, added human rabies vaccine to it’s portfolio. In this study, we estimated reported incidence of patients seeking PEP in relation to travel times to clinics provisioning PEP and extrapolate human rabies deaths in Madagascar. We find that PEP currently averts around 800 deaths each year, but that the burden remains high (1000 deaths/year), particularly in remote, hard-to-reach areas. We show that expanding PEP availability to more clinics could significantly reduce rabies deaths in Madagascar, but our results reaffirm that expansion alone is will not achieve the global goal of zero human deaths from dog-mediated rabies by 2030. Combining PEP expansion with outreach, surveillance, and mass dog vaccination programs will be necessary to move Madagascar, and other Low- and Middle-Income countries, forward on the path to rabies elimination.

Estimating malaria incidence from routine health facility-based surveillance data in Uganda

Background

Accurate measures of malaria incidence are essential to track progress and target high-risk populations. While health management information system (HMIS) data provide counts of malaria cases, quantifying the denominator for incidence using these data is challenging because catchment areas and care-seeking behaviours are not well defined. This study’s aim was to estimate malaria incidence using HMIS data by adjusting the population denominator accounting for travel time to the health facility.

Methods

Outpatient data from two public health facilities in Uganda (Kihihi and Nagongera) over a 3-year period (2011–2014) were used to model the relationship between travel time from patient village of residence (available for each individual) to the facility and the relative probability of attendance using Poisson generalized additive models. Outputs from the model were used to generate a weighted population denominator for each health facility and estimate malaria incidence. Among children aged 6 months to 11 years, monthly HMIS-derived incidence estimates, with and without population denominators weighted by probability of attendance, were compared with gold standard measures of malaria incidence measured in prospective cohorts.

Results

A total of 48,898 outpatient visits were recorded across the two sites over the study period. HMIS incidence correlated with cohort incidence over time at both study sites (correlation in Kihihi = 0.64, p < 0.001; correlation in Nagongera = 0.34, p = 0.045). HMIS incidence measures with denominators unweighted by probability of attendance underestimated cohort incidence aggregated over the 3 years in Kihihi (0.5 cases per person-year (PPY) vs 1.7 cases PPY) and Nagongera (0.3 cases PPY vs 3.0 cases PPY). HMIS incidence measures with denominators weighted by probability of attendance were closer to cohort incidence, but remained underestimates (1.1 cases PPY in Kihihi and 1.4 cases PPY in Nagongera).

Conclusions

Although malaria incidence measured using HMIS underestimated incidence measured in cohorts, even when adjusting for probability of attendance, HMIS surveillance data are a promising and scalable source for tracking relative changes in malaria incidence over time, particularly when the population denominator can be estimated by incorporating information on village of residence.

Routine data for malaria morbidity estimation in Africa: challenges and prospects

BACKGROUND

The burden of malaria in sub-Saharan Africa remains challenging to measure relying on epidemiological modelling to evaluate the impact of investments and providing an in-depth analysis of progress and trends in malaria response globally. In malaria-endemic countries of Africa, there is increasing use of routine surveillance data to define national strategic targets, estimate malaria case burdens and measure control progress to identify financing priorities. Existing research focuses mainly on the strengths of these data with less emphasis on existing challenges and opportunities presented.

CONCLUSION

Here we define the current imperfections common to routine malaria morbidity data at national levels and offer prospects into their future use to reflect changing disease burdens.

Mapping vaccination coverage to explore the effects of delivery mechanisms and inform vaccination strategies

The success of vaccination programs depends largely on the mechanisms used in vaccine delivery. National immunization programs offer childhood vaccines through fixed and outreach services within the health system and often, additional supplementary immunization activities (SIAs) are undertaken to fill gaps and boost coverage. Here, we map predicted coverage at 1 × 1 km spatial resolution in five low- and middle-income countries to identify areas that are under-vaccinated via each delivery method using Demographic and Health Surveys data. We compare estimates of the coverage of the third dose of diphtheria-tetanus-pertussis-containing vaccine (DTP3), which is typically delivered through routine immunization (RI), with those of measles-containing vaccine (MCV) for which SIAs are also undertaken. We find that SIAs have boosted MCV coverage in some places, but not in others, particularly where RI had been deficient, as depicted by DTP coverage. The modelling approaches outlined here can help to guide geographical prioritization and strategy design.

National and sub-national variation in patterns of febrile case management in sub-Saharan Africa

Given national healthcare coverage gaps, understanding treatment-seeking behaviour for fever is crucial for the management of childhood illness and to reduce deaths. Here, we conduct a modelling study triangulating household survey data for fever in children under the age of five years with georeferenced public health facility databases (n = 86,442 facilities) in 29 countries across sub-Saharan Africa, to estimate the probability of seeking treatment for fever at public facilities. A Bayesian item response theory framework is used to estimate this probability based on reported fever episodes, treatment choice, residence, and estimated travel-time to the nearest public-sector health facility. Findings show inter- and intra-country variation, with the likelihood of seeking treatment for fever less than 50% in 16 countries. Results highlight the need to invest in public healthcare and related databases. The variation in public sector use illustrates the need to include such modelling in future infectious disease burden estimation.

Methods of Population Spatialization Based on the Classification Information of Buildings from China's First National Geoinformation Survey in Urban Area: A Case Study of Wuchang District, Wuhan City, China

Most of the currently mature methods that are used globally for population spatialization are researched on a single level, and are dependent on the spatial relationship between population and land covers (city, road, water area, etc.), resulting in difficulties in data acquisition and an inability to identify precise features on the different levels. This paper proposes a multi-level population spatialization method on the different administrative levels with the support of China’s first national geoinformation survey, and then considers several approaches to verify the results of the multi-level method. This paper aims to establish a multi-level population spatialization method that is suitable for the administrative division of districts and streets. It is assumed that the same residential house has the same population density on the district level. Based on this assumption, the least squares regression model is used to obtain the optimized prediction model and accurate population space prediction results by dynamically segmenting and aggregating house categories.In addition, it is assumed that the distribution of the population is relatively regular in communities that are spatially close to each other, and that the population densities on the street level are similar, so the average population density is assessed by optimizing the community and surrounding residential houses on the street level. Finally, the scientificalness and rationality of the proposed method is proved by spatial autocorrelation analysis, overlay analysis, cross-validation analysis and accuracy assessment methods.

High resolution age-structured mapping of childhood vaccination coverage in low and middle income countries

BACKGROUND

The expansion of childhood vaccination programs in low and middle income countries has been a substantial public health success story. Indicators of the performance of intervention programmes such as coverage levels and numbers covered are typically measured through national statistics or at the scale of large regions due to survey design, administrative convenience or operational limitations. These mask heterogeneities and 'coldspots' of low coverage that may allow diseases to persist, even if overall coverage is high. Hence, to decrease inequities and accelerate progress towards disease elimination goals, fine-scale variation in coverage should be better characterized.

METHODS

Using measles as an example, cluster-level Demographic and Health Surveys (DHS) data were used to map vaccination coverage at 1 km spatial resolution in Cambodia, Mozambique and Nigeria for varying age-group categories of children under five years, using Bayesian geostatistical techniques built on a suite of publicly available geospatial covariates and implemented via Markov Chain Monte Carlo (MCMC) methods.

RESULTS

Measles vaccination coverage was found to be strongly predicted by just 4-5 covariates in geostatistical models, with remoteness consistently selected as a key variable. The output 1 × 1 km maps revealed significant heterogeneities within the three countries that were not captured using province-level summaries. Integration with population data showed that at the time of the surveys, few districts attained the 80% coverage, that is one component of the WHO Global Vaccine Action Plan 2020 targets.

CONCLUSION

The elimination of vaccine-preventable diseases requires a strong evidence base to guide strategies and inform efficient use of limited resources. The approaches outlined here provide a route to moving beyond large area summaries of vaccination coverage that mask epidemiologically-important heterogeneities to detailed maps that capture subnational vulnerabilities. The output datasets are built on open data and methods, and in flexible format that can be aggregated to more operationally-relevant administrative unit levels.