Descriptive Analysis of Measles Outbreak in Liberia, 2022.

Background: Liberia reported a large outbreak of measles involving all the counties in 2022. We conducted a descriptive analysis of the measles surveillance data to understand the trend of the outbreak and guide further policy action to prevent future outbreaks. Methods: We analyzed the measles surveillance data from Epi week 1 to 51, 2022. All the laboratory-confirmed cases, clinically compatible and epidemiologically linked cases were included in the analysis, the variables of interest included the patient's age, sex, place of residence, measles classification, measles vaccination status, and outcome. We cleaned and analyzed the data using R version 4.2.0 and Arc GIS Pro. The demographic characteristics of the cases were presented, the progression of the cases was presented in Epicurve and the spatial distribution and the case fatality rate (CFR) of the case were presented at the district level using the Arc GIS Pro. Results: The median age of the cases was 4 years (interquartile range: 2-8 years). Children under five years of age constituted 60% of the cases (4836/8127), and females accounted for 52% (4204/8127) of the cases. Only 1% (84/8127) of the cases had documentary evidence of receiving at least one dose of measles-containing vaccine (MCV). Only 3 out of 92 health districts in the country did not report a case of measles during the period under review. The overall cases fatality rate was 1% however CFR of up to 10% were reported in some districts. Conclusion: The outbreak of measles involved almost all the districts of the country, exposing a possible nationwide suboptimal immunization coverage for MCV. The high CFR reported in some districts needs further investigation.

HIV infection in Eastern and Southern Africa: Highest burden, largest challenges, greatest potential.

BACKGROUND: The burden of HIV is especially concerning for Eastern and Southern Africa (ESA), as despite expansion of test-and-treat programmes, this region continues to experience significant challenges resulting from high rates of morbidity, mortality and new infections. Hard-won lessons from programmes on the ground in ESA should be shared. OBJECTIVES: This report summarises relevant evidence and regional experts' recommendations regarding challenges specific to ESA. METHOD: This commentary includes an in-depth review of relevant literature, progress against global goals and consensus opinion from experts. RESULTS: Recommendations include priorities for essential research (surveillance data collection, key and vulnerable population education and testing, in-country testing trials and evidence-based support services to improve retention in care) as well as research that can accelerate progress towards the prevention of new infections and achieving ambitious global goals in ESA. CONCLUSION: The elimination of HIV in ESA will require continued investment, commitment to evidence-based programmes and persistence. Local research is critical to ensuring that responses in ESA are targeted, efficient and evaluated.

A systematic review of validated methods to capture myopericarditis using administrative or claims data.

PURPOSE: To identify algorithms that can capture incident cases of myocarditis and pericarditis in administrative and claims databases; these algorithms can eventually be used to identify cardiac inflammatory adverse events following vaccine administration. METHODS: We searched MEDLINE from 1991 to September 2012 using controlled vocabulary and key terms related to myocarditis. We also searched the reference lists of included studies. Two investigators independently assessed the full text of studies against pre-determined inclusion criteria. Two reviewers independently extracted data regarding participant and algorithm characteristics as well as study conduct. RESULTS: Nine publications (including one study reported in two publications) met criteria for inclusion. Two studies performed medical record review in order to confirm that these coding algorithms actually captured patients with the disease of interest. One of these studies identified five potential cases, none of which were confirmed as acute myocarditis upon review. The other study, which employed a search algorithm based on diagnostic surveillance (using ICD-9 codes 420.90, 420.99, 422.90, 422.91 and 429.0) and sentinel reporting, identified 59 clinically confirmed cases of myopericarditis among 492,671 United States military service personnel who received smallpox vaccine between 2002 and 2003. Neither study provided algorithm validation statistics (positive predictive value, sensitivity, or specificity). CONCLUSIONS: A validated search algorithm is currently unavailable for identifying incident cases of pericarditis or myocarditis. Several authors have published unvalidated ICD-9-based search algorithms that appear to capture myocarditis events occurring in the context of other underlying cardiac or autoimmune conditions.

Closing the quality gap: revisiting the state of the science (vol. 3: quality improvement interventions to address health disparities).

OBJECTIVE: This review evaluates the effectiveness of quality improvement (QI) strategies in reducing disparities in health and health care. DATA SOURCES: We identified papers published in English between 1983 and 2011 from the MEDLINE® database, the Cumulative Index of Nursing and Allied Health Literature (CINAHL), Web of Science Social Science Index, and PsycINFO. REVIEW METHODS: All abstracts and full-text articles were dually reviewed. Studies were eligible if they reported data on effectiveness of QI interventions on processes or health outcomes in the United States such that the impact on a health disparity could be measured. The review focused on the following clinical conditions: breast cancer, colorectal cancer, diabetes, heart failure, hypertension, coronary artery disease, asthma, major depressive disorder, cystic fibrosis, pneumonia, pregnancy, and end-stage renal disease. It assessed health disparities associated with race or ethnicity, socioeconomic status, insurance status, sexual orientation, health literacy/numeracy, and language barrier. We evaluated the risk of bias of individual studies and the overall strength of the body of evidence based on risk of bias, consistency, directness, and precision. RESULTS: Nineteen papers, representing 14 primary research studies, met criteria for inclusion. All but one of the studies incorporated multiple components into their QI approach. Patient education was part of most interventions (12 of 14), although the specific approach differed substantially across the studies. Ten of the studies incorporated self-management; this would include, for example, teaching individuals with diabetes to check their blood sugar regularly. Most (8 of 14) included some sort of provider education, which may have focused on the clinical issue or on raising awareness about disparities affecting the target population. Studies evaluated the effect of these strategies on disparities in the prevention or treatment of breast or colorectal cancer, cardiovascular disease, depression, or diabetes. Overall, QI interventions were not shown to reduce disparities. Most studies have focused on racial or ethnic disparities, with some targeted interventions demonstrating greater effect in racial minorities--specifically, supporting individuals in tracking their blood pressure at home to reduce blood pressure and collaborative care to improve depression care. In one study, the effect of a language-concordant breast cancer screening intervention was helpful in promoting mammography in Spanish-speaking women. For some depression care outcomes, the collaborative care model was more effective in less-educated individuals than in those with more education and in women than in men. CONCLUSIONS: The literature on QI interventions generally and their ability to improve health and health care is large. Whether those interventions are effective at reducing disparities remains unclear. This report should not be construed to assess the general effectiveness of QI in the health care setting; rather, QI has not been shown specifically to reduce known disparities in health care or health outcomes. In a few instances, some increased effect is seen in disadvantaged populations; these studies should be replicated and the interventions studied further as having potential to address disparities.