Exit strategies: optimising feasible surveillance for detection, elimination, and ongoing prevention of COVID-19 community transmission.

BACKGROUND: Following implementation of strong containment measures, several countries and regions have low detectable community transmission of COVID-19. We developed an efficient, rapid, and scalable surveillance strategy to detect remaining COVID-19 community cases through exhaustive identification of every active transmission chain. We identified measures to enable early detection and effective management of any reintroduction of transmission once containment measures are lifted to ensure strong containment measures do not require reinstatement. METHODS: We compared efficiency and sensitivity to detect community transmission chains through testing of the following: hospital cases; fever, cough and/or ARI testing at community/primary care; and asymptomatic testing; using surveillance evaluation methods and mathematical modelling, varying testing capacities, reproductive number (R) and weekly cumulative incidence of COVID-19 and non-COVID-19 respiratory symptoms using data from Australia. We assessed system requirements to identify all transmission chains and follow up all cases and primary contacts within each chain, per million population. RESULTS: Assuming 20% of cases are asymptomatic and 30% of symptomatic COVID-19 cases present for testing, with R = 2.2, a median of 14 unrecognised community cases (8 infectious) occur when a transmission chain is identified through hospital surveillance versus 7 unrecognised cases (4 infectious) through community-based surveillance. The 7 unrecognised community upstream cases are estimated to generate a further 55-77 primary contacts requiring follow-up. The unrecognised community cases rise to 10 if 50% of cases are asymptomatic. Screening asymptomatic community members cannot exhaustively identify all cases under any of the scenarios assessed. The most important determinant of testing requirements for symptomatic screening is levels of non-COVID-19 respiratory illness. If 4% of the community have respiratory symptoms, and 1% of those with symptoms have COVID-19, exhaustive symptomatic screening requires approximately 11,600 tests/million population using 1/4 pooling, with 98% of cases detected (2% missed), given 99.9% sensitivity. Even with a drop in sensitivity to 70%, pooling was more effective at detecting cases than individual testing under all scenarios examined. CONCLUSIONS: Screening all acute respiratory disease in the community, in combination with exhaustive and meticulous case and contact identification and management, enables appropriate early detection and elimination of COVID-19 community transmission. An important component is identification, testing, and management of all contacts, including upstream contacts (i.e. potential sources of infection for identified cases, and their related transmission chains). Pooling allows increased case detection when testing capacity is limited, even given reduced test sensitivity. Critical to the effectiveness of all aspects of surveillance is appropriate community engagement, messaging to optimise testing uptake and compliance with other measures.

Analysis of survival in HIV-infected subjects according to socio-economic resources in the HAART era.

Availability of Highly Active Anti-Retroviral Treatment (HAART) has modified the natural history of HIV infection, resulting in increase of seropositive subjects survival. The aim of the study was to assess patients' survival in relation to socio-economic status in HAART era using Functional Multidimensional Evaluation questionnaire. A three-level Socio-Economic Index (SEI) combining results from self-perception of unmet needs and objective data from the assessment of the two dimensions has been set up by the authors. Of the 382 subjects interviewed, 102 had been lost to follow-up. SEI showed that 66.4% of the sample faced unmet social or economic needs and 17.1% had unmet needs in both areas. There was a significant relationship between the self-sufficiency in performing Activities of Daily Living (ADL), Clinical Staging, CD4 cell count, SEI and risk of death. The lowest level of SEI was associated with a doubled risk of death compared to SEI upper level. Availability of social and economics support have a positive effect upon survival in patients with HIV infection, also in case of availability of HAART. The combination of subjective and objective assessment of socio-economic resources allows a better understanding of their impact on survival.