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The effect of the byssinosis controversy on surveillance programs in the cotton textile industry is reviewed. The federally regulated format for industry medical surveillance guarantees neither automatic reduction of cotton dust exposure for high-risk workers nor wage rate retention for workers who are transferred to less dusty job sites. The absence of universal guidelines for worker management, combined with doubt over the severity and prevalence of byssinosis, encourages employers to evaluate medical surveillance programs primarily on the basis of their economic impact. When employers use the programs to control their losses, the potential costs of worker participation are increased. Comparisons with medical surveillance programs in the coal industry suggest that health benefits to workers can be guaranteed in the context of disputes over occupational diseases if industry, labor, and government agencies all participate in program design and operation.

This study analyzes the 4-year phase-in of Medicaid Primary Care Case Management (PCCM) in Georgia and Alabama. The effect of PCCM implementation on children's primary and preventive care, independent of changes in Medicaid participating providers, was measured by race. Accounting for provider supply, PCCMwas associated with lower use of primary care for all children except white non-Hispanics in urban Georgia. In urban Alabama, PCCM reduced preventive care for white and black non-Hispanic children. This held only for blacks in urban Georgia, while PCCM was associated with increased preventive care among all children in rural Georgia. The negative effect of PCCM was further compounded by negative effects of reduced provider availability. Reductions in office-based Medicaid providers affected Alabama children more often, while reductions in hospital-based physicians had a negative effect for Georgia children. Implementation of PCCM without fee increases may have had unexpected negative effects that differentially affected minority children.

Neglected tropical diseases (NTDs) have long been overlooked in the global health agenda. The article is intended to generate information in consideration of the history of colonization of tropical countries with a special focus on tropical diseases especially common in the army during colonial wars and throughout the colonial era. Extreme poverty and warm tropical climates are the two most potent forces promoting the spread of neglected tropical diseases. European colonial doctors made valuable contribution towards understanding them and discovery these diseases. Large outbreaks of infectious and tropical diseases occurred in the Army throughout the colonial era, strongly influenced the formation of the Army Medical Services including provision for teaching and research. Subsequent improvements in prevention, diagnosis and treatment reduced the mortality from tropical diseases. Now in an era of "globalized" environment of interdependent trade, travel, migration, and international economic markets, many factors play an important role in the rise, emergence, and reemergence of tropical infectious disease, which necessitates a coordinated, global response. Many of the emerging and reemerging infectious diseases are also "neglected," meaning they impact the world's poorest and lack adequate funding and innovation for prevention and treatment, with some not adequately identified or studied. Although progress has been made in the management of neglected disease, there remains much work to be done. During the coming decade the global response will be able to further build on today's successes, align with the new global health and development frameworks. ; В статье рассматриваются исторические аспекты формирования тропической медицины, которая прошла путь от формального накопления знаний о тропической патологии, их предварительного анализа до открытия возбудителей и научного поиска мер борьбы. Широкий видовой спектр возбудителей паразитозов, благоприятный жаркий тропический климат в совокупности с низким ...

Fine-grained records of people's interactions, both offline and online, are collected at large scale. These data contain sensitive information about whom we meet, talk to, and when. We demonstrate here how people's interaction behavior is stable over long periods of time and can be used to identify individuals in anonymous datasets. Our attack learns the profile of an individual using geometric deep learning and triplet loss optimization. In a mobile phone metadata dataset of more than 40k people, it correctly identifies 52% of individuals based on their 2-hop interaction graph. We further show that the profiles learned by our method are stable over time and that 24% of people are still identifiable after 20 weeks. Our results suggest that people with well-balanced interaction graphs are more identifiable. Applying our attack to Bluetooth close-proximity networks, we show that even 1-hop interaction graphs are enough to identify people more than 26% of the time. Our results provide strong evidence that disconnected and even re-pseudonymized interaction data can be linked together making them personal data under the European Union's General Data Protection Regulation.

This study examines the impact of a Medicaid-supported intervention (Antenatal and Neonatal Guidelines, Education and Learning System) to expand a high-risk obstetrics consulting service on the use of specialty consults between 2001 and 2006. Using a Medicaid claims-birth certificate data set, we find a decline over time in use of specialty consults for lower risk diagnoses and a shift to remote modalities for contact. Local physician participation in grand rounds via teleconference was associated both with specialty contact and use of remote modalities. Local physician use of a Call Center service was also associated with patient specialty contact. Expansion of telemedicine remote sites did not increase the likelihood of contact but was associated with the shift toward remote modalities. Specialty consult use and modality were influenced by the care context of the patient, particularly level of pregnancy risk, the specialty of the primary prenatal care provider, the timing of her prenatal care, and her ethnicity and education level.

ACKNOWLEDGMENTS The authors would like to thank all of the patients and controls for participation in each of the studies. Equally, we thank all members of each of the study groups and other personnel for their contributions. Funding sources for the respective studies are as follows: The Norwegian ParkWest study has been funded by the Research Council of Norway (177966), the Western Norway Regional Health Authority (911218), the Norwegian Parkinson's Research Foundation, and Rebergs Legacy. PINE study was supported by Parkinson's UK (G0502, G0914, G1302), Scottish Government Chief Scientist Office, BMA Doris Hillier Award, the BUPA Foundation, NHS Grampian Endowments, and RS MacDonald Trust. The NYPUM study has been funded by the Swedish Medical Research Council, the Swedish Parkinson's disease Association, the Swedish Parkinson's Foundation, Parkinson Research Foundation, Erling Persson Foundation, Kempe Foundation, the Swedish Brain Foundation (Hjarnfonden), and the Vasterbotten County Council. AAS, JMG and GA are supported by the Research Council of Norway (287842). BLF acknowledges support through donations to the UCLA Clinical Neurogenomics Research Center. CK is supported by the NIH grant F32AG063442. The PEG study was supported by NIH/NIEHS grants R01-ES010544 and U54-ES012078. Publication of this manuscript was supported under the The Michael J. Fox Foundation: 2021 RFA: Accelerating Publication of Parkinson's Disease Replication Data. ; Peer reviewed ; Publisher PDF