One size does not fit all: an application of stochastic modeling to estimating primary healthcare needs in Ethiopia at the sub-national level.

BACKGROUND: Primary healthcare systems require adequate staffing to meet the needs of their local population. Guidelines typically use population ratio targets for healthcare workers, such as Ethiopia's goal of two health extension workers for every five thousand people. However, fixed ratios do not reflect local demographics, fertility rates, disease burden (e.g., malaria endemicity), or trends in these values. Recognizing this, we set out to estimate the clinical workload to meet the primary healthcare needs in Ethiopia by region. METHODS: We utilize the open-source R package PACE-HRH for our analysis, which is a stochastic Monte Carlo simulation model that estimates workload for a specified service package and population. Assumptions and data inputs for region-specific fertility, mortality, disease burden were drawn from literature, DHS, and WorldPop. We project workload until 2035 for seven regions and two charted cities of Ethiopia. RESULTS: All regions and charted cities are expected to experience increased workload between 2021 and 2035 for a starting catchment of five thousand people. The expected (mean) annual clinical workload varied from 2,930 h (Addis) to 3,752 h (Gambela) and increased by 19-28% over fifteen years. This results from a decline in per capita workload (due to declines in fertility and infectious diseases), overpowered by total population growth. Pregnancy, non-communicable diseases, sick child care, and nutrition remain the largest service categories, but their priority shifts substantially in some regions by 2035. Sensitivity analysis shows that fertility assumptions have major implications for workload. We incorporate seasonality and estimate monthly variation of up to 8.9% (Somali), though most services with high variability are declining. CONCLUSIONS: Regional variation in demographics, fertility, seasonality, and disease trends all affect the workload estimates. This results in differences in expected clinical workload, the level of uncertainty in those estimates, and relative priorities between service categories. By showing these differences, we demonstrate the inadequacy of a fixed population ratio for staffing allocation. Policy-makers and regulators need to consider these factors in designing their healthcare systems, or they risk sub-optimally allocating workforce and creating inequitable access to care.

Estimates of the cost to build a stand-alone environmental surveillance system for typhoid in low- and middle-income countries.

The typhoid conjugate vaccine is a safe and effective method for preventing Salmonella enterica serovar Typhi (typhoid) and the WHO's guidance supports its use in locations with ongoing transmission. However, many countries lack a robust clinical surveillance system, making it challenging to determine where to use the vaccine. Environmental surveillance is one alternative approach to identify ongoing transmission, but the cost to implement such a strategy is previously unknown. This paper estimated the cost of setting up and operating an environmental surveillance program for thirteen protocols that are in development, including thirteen cost components and twenty-seven pieces of equipment. Unit costs were obtained from research labs involved in protocol development and equipment information was obtained from manufacturers and the expert opinion of individuals in participating labs. We used Monte Carlo simulations to estimate the costs and the input parameters were modeled as distributions to incorporate the uncertainty. Total costs per sample including setup, overhead, and operational costs, range from $357-794 at a scale of 25 sites to $116-532 at 125 sites. Operational costs (ongoing expenditures) range from $218-584 per sample at a scale of 25 sites to $74-421 at 125 sites. Eleven of the thirteen protocols have operational costs below $200, at this higher scale. Protocols with higher up-front equipment costs benefit more from scale efficiencies and sensitivity analyses show that laboratory labor, processes, and consumables are the primary drivers of uncertainty. At scale, environmental surveillance for typhoid may be affordable (depending on the protocol, scale, and geographic context), though cost will need to be considered alongside future evaluations of test sensitivity. Opportunities to leverage existing infrastructure and multi-disease platforms may be necessary to further reduce costs.

Assessing the characteristics of un- and under-vaccinated children in low- and middle-income countries: A multi-level cross-sectional study.

Achieving equity in vaccination coverage has been a critical priority within the global health community. Despite increased efforts recently, certain populations still have a high proportion of un- and under-vaccinated children in many low- and middle-income countries (LMICs). These populations are often assumed to reside in remote-rural areas, urban slums and conflict-affected areas. Here, we investigate the effects of these key community-level factors, alongside a wide range of other individual, household and community level factors, on vaccination coverage. Using geospatial datasets, including cross-sectional data from the most recent Demographic and Health Surveys conducted between 2008 and 2018 in nine LMICs, we fitted Bayesian multi-level binary logistic regression models to determine key community-level and other factors significantly associated with non- and under-vaccination. We analyzed the odds of receipt of the first doses of diphtheria-tetanus-pertussis (DTP1) vaccine and measles-containing vaccine (MCV1), and receipt of all three recommended DTP doses (DTP3) independently, in children aged 12-23 months. In bivariate analyses, we found that remoteness increased the odds of non- and under-vaccination in nearly all the study countries. We also found evidence that living in conflict and urban slum areas reduced the odds of vaccination, but not in most cases as expected. However, the odds of vaccination were more likely to be lower in urban slums than formal urban areas. Our multivariate analyses revealed that the key community variables-remoteness, conflict and urban slum-were sometimes associated with non- and under-vaccination, but they were not frequently predictors of these outcomes after controlling for other factors. Individual and household factors such as maternal utilization of health services, maternal education and ethnicity, were more common predictors of vaccination. Reaching the Immunisation Agenda 2030 target of reducing the number of zero-dose children by 50% by 2030 will require country tailored analyses and strategies to identify and reach missed communities with reliable immunisation services.

Estimates of the number and distribution of zero-dose and under-immunised children across remote-rural, urban, and conflict-affected settings in low and middle-income countries.

While there has been great success in increasing the coverage of new childhood vaccines globally, expanding routine immunization to reliably reach all children and communities has proven more challenging in many low- and middle-income countries. Achieving this requires vaccination strategies and interventions that identify and target those unvaccinated, guided by the most current and detailed data regarding their size and spatial distribution. Through the integration and harmonisation of a range of geospatial data sets, including population, vaccination coverage, travel-time, settlement type, and conflict locations. We estimated the numbers of children un- or under-vaccinated for measles and diphtheria-tetanus-pertussis, within remote-rural, urban, and conflict-affected locations. We explored how these numbers vary both nationally and sub-nationally, and assessed what proportions of children these categories captured, for 99 lower- and middle-income countries, for which data was available. We found that substantial heterogeneities exist both between and within countries. Of the total 14,030,486 children unvaccinated for DTP1, over 11% (1,656,757) of un- or under-vaccinated children were in remote-rural areas, more than 28% (2,849,671 and 1,129,915) in urban and peri-urban areas, and up to 60% in other settings, with nearly 40% found to be within 1-hour of the nearest town or city (though outside of urban/peri-urban areas). Of the total number of those unvaccinated, we estimated between 6% and 15% (826,976 to 2,068,785) to be in conflict-affected locations, based on either broad or narrow definitions of conflict. Our estimates provide insights into the inequalities in vaccination coverage, with the distributions of those unvaccinated varying significantly by country, region, and district. We demonstrate the need for further inquiry and characterisation of those unvaccinated, the thresholds used to define these, and for more country-specific and targeted approaches to defining such populations in the strategies and interventions used to reach them.

Projection of Costs of Polio Eradication Compared to Permanent Control.

Despite increased efforts and spending toward polio eradication, it has yet to be eliminated worldwide. We aimed to project economic costs of polio eradication compared to permanent control. We used historical Financial Resource Requirements from the Global Polio Eradication Initiative, as well as vaccination and population data from publicly available sources, to project costs for routine immunization, immunization campaigns, surveillance and laboratory resources, technical assistance, social mobilization, treatment, and overhead. We found that cumulative spending for a control strategy would exceed that for an eradication strategy in 2032 (range, 2027-2051). Eradication of polio would likely be cost-saving compared to permanent control.

The cost saving opportunity of introducing a card review into measles-containing vaccination campaigns.

Measles vaccination is a cost-effective way to prevent infection and reduce mortality and morbidity. However, in countries with fragile routine immunization infrastructure, coverage rates are still low and supplementary immunization campaigns (SIAs) are used to reach previously unvaccinated children. During campaigns, vaccine is generally administered to every child, regardless of their vaccination status and as a result, there is the possibility that a child that is already immune to measles (i.e. who has had 2+ vaccinations) would receive an unnecessary dose, resulting in excess cost. Selective vaccination has been proposed as one solution to this; children who were able to provide documentation of previous vaccination would not be vaccinated repeatedly. While this would result in reduced vaccine and supply cost, it would also require additional staff time and increased social mobilization investment, potentially outweighing the benefits. We utilize Monte Carlo simulation to assess under what conditions a selective vaccination policy would indeed result in net savings. We demonstrate that cost savings are possible in contexts with a high joint probability of an individual child having both 2+ previous measles doses and also an available record. We also find that the magnitude of net cost savings is highly dependent on whether a country is using measles-only or measles-rubella vaccine and on the required skill set of the individual who would review the previous vaccination records.

Optimization of frequency and targeting of measles supplemental immunization activities in Nigeria: A cost-effectiveness analysis.

BACKGROUND: Measles causes significant childhood morbidity in Nigeria. Routine immunization (RI) coverage is around 40% country-wide, with very high levels of spatial heterogeneity (3-86%), with supplemental immunization activities (SIAs) at 2-year or 3-year intervals. We investigated cost savings and burden reduction that could be achieved by adjusting the inter-campaign interval by region. METHODS: We modeled 81 scenarios; permuting SIA calendars of every one, two, or three years in each of four regions of Nigeria (North-west, North-central, North-east, and South). We used an agent-based disease transmission model to estimate the number of measles cases and ingredients-based cost models to estimate RI and SIA costs for each scenario over a 10 year period. RESULTS: Decreasing SIAs to every three years in the North-central and South (regions of above national-average RI coverage) while increasing to every year in either the North-east or North-west (regions of below national-average RI coverage) would avert measles cases (0.4 or 1.4 million, respectively), and save vaccination costs (save $19.4 or $5.4 million, respectively), compared to a base-case of national SIAs every two years. Decreasing SIA frequency to every three years in the South while increasing to every year in the just the North-west, or in all Northern regions would prevent more cases (2.1 or 5.0 million, respectively), but would increase vaccination costs (add $3.5 million or $34.6 million, respectively), for $1.65 or $6.99 per case averted, respectively. CONCLUSIONS: Our modeling shows how increasing SIA frequency in Northern regions, where RI is low and birth rates are high, while decreasing frequency in the South of Nigeria would reduce the number of measles cases with relatively little or no increase in vaccination costs. A national vaccination strategy that incorporates regional SIA targeting in contexts with a high level of sub-national variation would lead to improved health outcomes and/or lower costs.

Modeling the economic impact of different vial-opening thresholds for measles-containing vaccines.

INTRODUCTION: The lack of specific policies on how many children must be present at a vaccinating location before a healthcare worker can open a measles-containing vaccine (MCV) - i.e. the vial-opening threshold - has led to inconsistent practices, which can have wide-ranging systems effects. METHODS: Using HERMES-generated simulation models of the routine immunization supply chains of Benin, Mozambique and Niger, we evaluated the impact of different vial-opening thresholds (none, 30% of doses must be used, 60%) and MCV presentations (10-dose, 5-dose) on each supply chain. We linked these outputs to a clinical- and economic-outcomes model which translated the change in vaccine availability to associated infections, medical costs, and DALYs. We calculated the economic impact of each policy from the health system perspective. RESULTS: The vial-opening threshold that maximizes vaccine availability while minimizing costs varies between individual countries. In Benin (median session size = 5), implementing a 30% vial-opening threshold and tailoring distribution of 10-dose and 5-dose MCVs to clinics based on session size is the most cost-effective policy, preventing 671 DALYs ($471/DALY averted) compared to baseline (no threshold, 10-dose MCVs). In Niger (median MCV session size = 9), setting a 60% vial-opening threshold and tailoring MCV presentations is the most cost-effective policy, preventing 2897 DALYs ($16.05/ DALY averted). In Mozambique (median session size = 3), setting a 30% vial-opening threshold using 10-dose MCVs is the only beneficial policy compared to baseline, preventing 3081 DALYs ($85.98/DALY averted). Across all three countries, however, a 30% vial-opening threshold using 10-dose MCVs everywhere is the only MCV threshold that consistently benefits each system compared to baseline. CONCLUSION: While the ideal vial-opening threshold policy for MCV varies by supply chain, implementing a 30% vial-opening threshold for 10-dose MCVs benefits each system by improving overall vaccine availability and reducing associated medical costs and DALYs compared to no threshold.