Background In many countries, patients with mild coronavirus disease 2019 (COVID-19) are told to self-isolate at home, but imperfect compliance and shared living space with uninfected people limit the effectiveness of home-based isolation. We aim to examine the impact of facility-based isolation compared to self-isolation at home on the continuing epidemic in the United States. Methods We developed a compartment model to simulate the dynamic transmission of COVID-19 and calibrated it to key epidemic measures in the United States from March to September. We simulated facility-based isolation strategies with various capacities and starting times under different diagnosis rates. The primary model outcomes included the reduction of new infections and deaths over two months from October onwards. We further explored different effects of facility-based isolation under different epidemic burdens by major US Census Regions, and performed sensitivity analyses by varying key model assumptions and parameters. Results We projected that facility-based isolation with moderate capacity of 5 beds per 10 000 total population could avert 4.17 (95% Credible Interval 1.65–7.11) million new infections and 16 000 (8000-23 000) deaths in two months compared with home-based isolation, equivalent to relative reductions of 57% (44–61%) in new infections and 37% (27–40%) in deaths. Facility-based isolation with high capacity of 10 beds per 10 000 population would achieve greater reduction of 76% (62–84%) in new infections and 52% (37–64%) in deaths when supported by the expanded testing with a 20% daily diagnosis rate. Delays in implementation would substantially reduce the impact of facility-based isolation. The effective capacity and the impact of facility-based isolation varied by epidemic stage across regions. Conclusion Timely facility-based isolation for mild COVID-19 cases could substantially reduce the number of new infections and effectively curb the continuing epidemic compared to home-based isolation. The local epidemic burden should determine the effective scale of facility-based isolation strategies.

Background China’s long-term care insurance (LTCI) policy has been minimally evaluated. This systematic review aimed to assess the impact of China’s LTCI pilot on beneficiaries and their caregivers. Methods This review is based on a search of peer-reviewed studies in English (Embase, MEDLINE, Web of Science) and Chinese (China National Knowledge Infrastructure [CNKI], VIP, Wanfang) databases from January 2016 through July 2020, with all studies published in English or Chinese included. We included quantitative analyses of beneficiary-level data that assessed the impact of LTCI on beneficiaries and their caregivers, with no restriction placed on the outcomes studied. Results Nine studies met our inclusion criteria. One study was a randomised trial and two used quasi-experimental approaches. Four studies examined LTCI’s effect on beneficiaries’ quality of life, physical pain, and health service utilisation; one study reported the effect on beneficiaries’ healthcare expenditures; and one study evaluated the impact on caregivers’ care tasks. These studies generally found LTCI to be associated with an improvement in patients’ quality of life (including decreased physical pain), a reduction in the number of outpatient visits and hospitalisations, decreased patient-level health expenditures (e.g. one study reported a reduction in the length of stay, inpatient expenditures, and health insurance expenditures in tertiary hospitals by 41.0%, 17.7%, and 11.4%, respectively), and reduced informal care tasks for caregivers. In addition, four out of four studies that evaluated this outcome found that beneficiaries’ overall satisfaction with LTCI was high. Conclusion The current evidence base for the effects of LTCI in China on beneficiaries and their caregivers is sparse. Nonetheless, the existing studies suggest that LTCI has positive effects on beneficiaries and their caregivers. Further rigorous research on the impacts of LTCI in China is needed to inform the future expansion of the program.

The Pickup and Delivery Problem with Time Windows (PDPTW) is a generalization of the well studied Vehicle Routing Problem with Time Windows (VRPTW). This paper studies a Grouping Genetic Algorithm for solving the PDPTW. The insertionsearching heuristics (in GGA) which can generate feasible solutions was improved, new data structures were built, and then three routing adjustment strategies were added to come up with the Multi-Strategy Grouping Genetic Algorithm (MSGGA). The PDPTW benchmark problems with 100 customers are calculated with MSGGA, and the comparison between the result and that of the reference shows that the new algorithm shortens the calculating time with its astringency, better solutions of four cases are obtained and stability is improved.

No abstract

This study sought to analyse tyrosinase (TYR) pathogenic variants in a Chinese Mongolian family with progressive symmetric erythrokeratoderma (PSEK). We collected clinical data and peripheral blood DNA samples from the initial patient and his family members for polymerase chain reaction (PCR) amplification and whole-exome sequencing of the coding region of TYR. Genetic analysis showed a TYR insertion (c. 929_930insC; p.Arg311Lysfs*7) in the patient that was not detected in any of the normal family members or in 100 healthy controls. This report provides the first description of this TYR pathogenic variant (c. 929_930insC) in a family; functional studies and further research are needed for an in-depth analysis.