Evaluating urban-rural access to pathology and laboratory medicine services in Tanzania.

Placement of pathology and laboratory medicine (PALM) services requires balancing efficiency (maximizing test volume) with equitable urban-rural access. We compared the association between population density (proxy for efficiency) and travel time to the closest facility (proxy for equitable access) across levels of Tanzania's public sector health system. We linked geospatial data for Tanzania from multiple sources.

Geospatial evaluation of trade-offs between equity in physical access to healthcare and health systems efficiency.

Introduction: Decisions regarding the geographical placement of healthcare services require consideration of trade-offs between equity and efficiency, but few empirical assessments are available. We applied a novel geospatial framework to study these trade-offs in four African countries.

Methods: Geolocation data on population density (a surrogate for efficiency), health centres and cancer referral centres in Kenya, Malawi, Tanzania and Rwanda were obtained from online databases.

Histology and Cytopathology Capacity in the Public Health Sector in Kenya.

Purpose: Histology and cytopathology services are necessary for cancer diagnosis and treatment. However, the current capacity of Kenya's pathology laboratories is unknown. A national survey was conducted among public sector pathology laboratories to assess their capacity to perform histology, fine-needle aspiration, and bone marrow aspiration.

Age-Standardized Mortality Rates in the Caribbean: One Source, Three Different Interpretations.

Purpose A recent publication in Morbidity and Mortality Weekly Report ( MMWR) provided the opportunity to calculate differences in published cancer mortality estimates for Caribbean jurisdictions from three organizations: MMWR, the International Agency for Research on Cancer, and the Institute for Health Metrics and Evaluation. This comparison study serves to educate end users of these data. Methods We downloaded the publicly available cancer mortality estimates for 15 jurisdictions and the United States from the three organizations.

Improving pathology and laboratory medicine in low-income and middle-income countries: roadmap to solutions.

Insufficient awareness of the centrality of pathology and laboratory medicine (PALM) to a functioning health-care system at policy and governmental level, with the resultant inadequate investment, has meant that efforts to enhance PALM in low-income and middle-income countries have been local, fragmented, and mostly unsustainable. Responding to the four major barriers in PALM service delivery that were identified in the first paper of this Series (workforce, infrastructure, education and training, and quality assurance), this second paper identifies potential solutions that can be applied in low-income and middle-income countries (LMICs). Increasing and retaining a quality PALM workforce requires access to mentorship and continuing professional development, task sharing, and the development of short-term visitor programmes.

Global Health Pathology Research: Purpose and Funding.

Like in all areas of science, it is important for funders and investigators of pathology to work together to develop a well-designed, well-executed clinical research agenda. In the first section of this article, the authors discuss how the National Institutes of Health (NIH) peer-review process applies to global health pathology research projects. Then, the authors present an illustrative sampling of NIH-funded projects with performance sites in low- and middle-income countries with 2 examples focused on cancer and anatomic pathology.

Multiple hypothesis testing and the declining-population paradigm in Steller sea lions.

We describe a novel spatially and temporally detailed approach for determining the cause or causes of a population decline, using the western Alaskan population of Steller sea lions (Eumetopias jubatus) as an example. Existing methods are mostly based on regression, which limits their utility when there are multiple hypotheses to consider and the data are sparse and noisy. Our likelihood-based approach is unbiased with regard to sample size, and its posterior probability landscape allows for the separate consideration of magnitude and certainty for multiple factors simultaneously.