Malaria risk factors and care-seeking behaviour within the private sector among high-risk populations in Vietnam: a qualitative study

BackgroundVietnam has successfully reduced malaria incidence by more than 90% over the past 10 years, and is now preparing for malaria elimination. However, the remaining malaria burden resides in individuals that are hardest to reach, in highly remote areas, where many malaria cases are treated through the informal private sector and are not reported to public health systems. This qualitative study aimed to contextualize and characterize the role of private providers, care-seeking behaviour of individuals at high risk of malaria, as well as risk factors that should be addressed through malaria elimination programmes in Vietnam.MethodsSemi-structured qualitative interviews were conducted with 11 key informants in Hanoi, 30 providers, 9 potential patients, and 11 individuals at risk of malaria in Binh Phuoc and Kon Tum provinces. Audio recorded interviews were transcribed and uploaded to Atlas TI™, themes were identified, from which programmatic implications and recommendations were synthesized.ResultsQualitative interviews revealed that efforts for malaria elimination in Vietnam should concentrate on reaching highest-risk populations in remote areas as well their care providers, in particular private pharmacies, private clinics, and grocery stores. Among these private providers, diagnosis is currently based on symptoms, leaving unconfirmed cases that are not reported to public health surveillance systems. Among at-risk individuals, knowledge of malaria was limited, and individuals reported not taking full courses of treatment, a practice that threatens selection for drug resistance. Access to insecticide-treated hammock nets, a potentially important preventive measure for settings with outdoor biting Anopheles vectors, was also limited.ConclusionsMalaria elimination efforts in Vietnam can be accelerated by targeting improved treatment, diagnosis, and reporting practices to private pharmacies, private clinics, and grocery stores. Programmes should also seek to increase awareness and understanding of malaria among at-risk populations, in particular the importance of using preventive measures and adhering to complete courses of anti-malarial medicines

Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization

Despite their promise, circulating tumor DNA (ctDNA)-based assays for multi-cancer early detection face challenges in test performance, due mostly to the limited abundance of ctDNA and its inherent variability. To address these challenges, published assays to date demanded a very high-depth sequencing, resulting in an elevated price of test. Herein, we developed a multimodal assay called SPOT-MAS (screening for the presence of tumor by methylation and size) to simultaneously profile methylomics, fragmentomics, copy number, and end motifs in a single workflow using targeted and shallow genome-wide sequencing (~0.55×) of cell-free DNA. We applied SPOT-MAS to 738 non-metastatic patients with breast, colorectal, gastric, lung, and liver cancer, and 1550 healthy controls. We then employed machine learning to extract multiple cancer and tissue-specific signatures for detecting and locating cancer. SPOT-MAS successfully detected the five cancer types with a sensitivity of 72.4% at 97.0% specificity. The sensitivities for detecting early-stage cancers were 73.9% and 62.3% for stages I and II, respectively, increasing to 88.3% for non-metastatic stage IIIA. For tumor-of-origin, our assay achieved an accuracy of 0.7. Our study demonstrates comparable performance to other ctDNA-based assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening

Mass Reproducibility and Replicability: A New Hope

This study pushes our understanding of research reliability by reproducing and replicating claims from 110 papers in leading economic and political science journals. The analysis involves computational reproducibility checks and robustness assessments. It reveals several patterns. First, we uncover a high rate of fully computationally reproducible results (over 85%). Second, excluding minor issues like missing packages or broken pathways, we uncover coding errors for about 25% of studies, with some studies containing multiple errors. Third, we test the robustness of the results to 5,511 re-analyses. We find a robustness reproducibility of about 70%. Robustness reproducibility rates are relatively higher for re-analyses that introduce new data and lower for re-analyses that change the sample or the definition of the dependent variable. Fourth, 52% of re-analysis effect size estimates are smaller than the original published estimates and the average statistical significance of a re-analysis is 77% of the original. Lastly, we rely on six teams of researchers working independently to answer eight additional research questions on the determinants of robustness reproducibility. Most teams find a negative relationship between replicators' experience and reproducibility, while finding no relationship between reproducibility and the provision of intermediate or even raw data combined with the necessary cleaning codes