Mapping maternal mortality rate via spatial zero-inflated models for count data: A case study of facility-based maternal deaths from Mozambique

A consolidated and geolocated facility list in Senegal from triangulating secondary data

Having a geolocated list of all facilities in a country - a "master facility list" (MFL) - can provide critical inputs for health program planning and implementation. To the best of our knowledge, Senegal has never had a centralized MFL, though many data sources currently exist within the broader Senegalese data landscape that could be leveraged and consolidated into a single database - a critical first step toward building a full MFL. We collated 12,965 facility observations from 16 separate datasets and lists in Senegal, and applied matching algorithms, manual checking and revisions as needed, and verification processes to identify unique facilities and triangulate corresponding GPS coordinates. Our resulting consolidated facility list has a total of 4,685 facilities, with 2,423 having at least one set of GPS coordinates. Developing approaches to leverage existing data toward future MFL establishment can help bridge data demands and inform more targeted approaches for completing a full facility census based on areas and facility types with the lowest coverage. Going forward, it is crucial to ensure routine updates of current facility lists, and to strengthen government-led mechanisms around such data collection demands and the need for timely data for health decision-making.

Transitioning from the "Three Delays" to a focus on continuity of care: a qualitative analysis of maternal deaths in rural Pakistan and Mozambique

BACKGROUND

The Three Delays Framework was instrumental in the reduction of maternal mortality leading up to, and during the Millennium Development Goals. However, this paper suggests the original framework might be reconsidered, now that most mothers give birth in facilities, the quality and continuity of the clinical care is of growing importance.

METHODS

The paper explores the factors that contributed to maternal deaths in rural Pakistan and Mozambique, using 76 verbal autopsy narratives from the Community Level Interventions for Pre-eclampsia (CLIP) Trial.

RESULTS

Qualitative analysis of these maternal death narratives in both countries reveals an interplay of various influences, such as, underlying risks and comorbidities, temporary improvements after seeking care, gaps in quality care in emergencies, convoluted referral systems, and arrival at the final facility in critical condition. Evaluation of these narratives helps to reframe the pathways of maternal mortality beyond a single journey of care-seeking, to update the categories of seeking, reaching and receiving care.

CONCLUSIONS

There is a need to supplement the pioneering "Three Delays Framework" to include focusing on continuity of care and the "Four Critical Connection Points": (1) between the stages of pregnancy, (2) between families and health care workers, (3) between health care facilities and (4) between multiple care-seeking journeys.

TRIAL REGISTRATION

NCT01911494, Date Registered 30/07/2013.

Mapping the Relative Risk of Congenital Hypothyroidism Incidence via Spatial Zero-Inflated Poisson Model in Guilan Province, Iran

Background:

Congenital hypothyroidism (CH) is one of the most prevalent preventable causes of mental retardation. Studies show that the incidence rate of CH is very high in Iran. Disease mapping is a tool for visually expressing the frequency, incidence, or relative risk of illness. The present study aimed to model CH counts considering the effects of the neighborhood in towns and perform mapping based on the relative risk.

Methods:

In this historical cohort study, data of all neonates diagnosed with CH with TSH level ≥5 mIU/L between March 21, 2017, and March 20, 2018, in health centers in Guilan, Iran were used. The number of neonates with CH was zero in most towns of Guilan Province. The Bayesian spatial zero-inflated Poisson (ZIP) regression model was employed to investigate the effect of the town's neighborhood on the relative risk of CH incidence. Then, the map of the posterior mean of the relative risk for CH incidence was provided. The analysis was performed using OpenBUGS and Arc GIS software programs.

Results:

The relative risk of CH incidence was high in the West of Guilan. Moreover, the goodness-of-fit criterion indicated that it is more appropriate to fit the Bayesian spatial ZIP model to these data than the common model.

Conclusions:

Considering the high relative risk of CH in the Western towns of Guilan Province, it is better to check important risk factors in this region.

A Bayesian approach for estimating age-adjusted rates for low-prevalence diseases over space and time

Age-adjusted rates are frequently used by epidemiologists to compare disease incidence and mortality across populations. In small geographic regions, age-adjusted rates computed directly from the data are subject to considerable variability and are generally unreliable. Therefore, we desire an approach that accounts for the excessive number of zero counts in disease mapping datasets, which are naturally present for low-prevalence diseases and are further innated when stratifying by age group. Bayesian modeling approaches are naturally suited to employ spatial and temporal smoothing to produce more stable estimates of age-adjusted rates for small areas. We propose a Bayesian hierarchical spatio-temporal hurdle model for counts and demonstrate how age-adjusted rates can be estimated from the hurdle model. We perform a simulation study to evaluate the performance of the proposed model vs a traditional Poisson model on datasets with varying characteristics. The approach is illustrated using two applications to cancer mortality at the county level.