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Background: The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) releases nucleocapsid proteins (NP) into the blood circulation in infected patients. We investigated whether plasma NP analysis could be used for diagnosing an infection and used for nosocomial screening. Methods: We collected blood samples from patients admitted to the hospital during a period with reverse transcription polymerase chain reaction (RT-PCR) based-screening of patients for SARS-CoV-2. Retrospectively the SARS-CoV-2 NP plasma concentrations were measured with an enzyme-linked immunosorbent assay (ELISA) method and used for an initial time course study to find the optimal time-point for sampling blood. Next, we estimated the diagnostic accuracy i.e. the clinical sensitivity and specificity at different plasma NP cut-off concentrations. Results: The time course study revealed profiles with rapid or more slow declines in NP titers after the RT-PCR result. Nevertheless, in the time interval 0 – 7 days after the RT-PCR result, the NP concentration was always above the level of detection at 1.66 pg/ml suggesting that the diagnosis could be established in the time interval of 0 - 7 days. The median time gap between the plasma NP and RT-PCR results was 0.0 days (n = 1957, interval: -26 to + 21 days). Reducing the time gap to seven days, the clinical sensitivity was 90.0% (n= 60, 95% CI, 82.4% to 97.6%) at a specificity of 95.9% (n=1876, 95% CI, 95.0% to 96.8%). Curve analysis by receiver operation characteristics identified a cut-off concentration of 1.87 pg/mL NP as optimal resulting in a positive predictive value of 41.2%, a negative predictive value of 99.7% and a prevalence of 3.1%. Conclusions: In conclusion, the NP method is acceptable for making the laboratory diagnosis of SARS-CoV-2, and an intended use of plasma NP as a prospective nosocomial screening method is considered feasible.

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Climate change is associated with adverse mental and emotional health outcomes. Social and economic factors are well-known drivers of mental health, yet comparatively few studies examine the social and economic pathways through which climate change affects mental health. There is additionally a lack of research on climate change and mental health in sub-Saharan Africa. This qualitative study aimed to identify potential social and economic pathways through which climate change impacts mental and emotional wellbeing, focusing on a vulnerable population of Kenyan smallholder farmers living with HIV. We conducted in-depth, semi-structured interviews with forty participants to explore their experience of climate change. We used a thematic analytical approach. We find that among our study population of Kenyan smallholder farmers living with HIV, climate change is significantly affecting mental and emotional wellbeing. Respondents universally report some level of climate impact on emotional health including high degrees of stress; fear and concern about the future; and sadness, worry, and anxiety from losing one’s home, farm, occupation, or ability to support their family. Climate-related economic insecurity is a main driver of emotional distress. Widespread economic insecurity disrupts systems of communal and family support, which is an additional driver of worsening mental and emotional health. Our study finds that individual adaptive strategies used by farmers in the face of economic and social volatility can deepen economic insecurity and are likely insufficient to protect mental health. Finally, we find that agricultural policies can worsen economic insecurity and other mental health risk factors. Our proposed conceptual model of economic and social pathways relevant for mental health can inform future studies of vulnerable populations and inform health system and policy responses to protect health in a changing climate.