Health systems resilience is key to learning lessons from country responses to crises such as coronavirus disease 2019 (COVID-19). In this perspective, we review COVID-19 responses in 28 countries using a new health systems resilience framework. Through a combination of literature review, national government submissions and interviews with experts, we conducted a comparative analysis of national responses. We report on domains addressing governance and financing, health workforce, medical products and technologies, public health functions, health service delivery and community engagement to prevent and mitigate the spread of COVID-19. We then synthesize four salient elements that underlie highly effective national responses and offer recommendations toward strengthening health systems resilience globally.
Photocatalytic production of H 2 O 2 from the reduction of O 2 by semiconductor photocatalysts (e.g., graphitic carbon nitride, C 3 N 4 ) has been regarded as an alternative for small-scale decentralized H 2 O 2 production. However, the efficiency of pristine C 3 N 4 photocatalysts is still limited by the narrow light absorption range and rapid charge recombination. Here, we presented a facile approach to simultaneously enhance the light absorption and promote the charge separation by introducing alkali metal dopants and N vacancies on C 3 N 4 . The introduction of alkali metal dopants and N vacancies successfully broadened the light absorption range, reduced the band gap from 2.85 to 2.63 eV, and greatly inhibited the charge recombination. The synergistic effect of doping and defect resulted in the improvement of photocatalytic performance with a H 2 O 2 production rate of 10.2 mmol/h/g, which is 89.5 times that of pristine C 3 N 4 . Thus, this work not only gives insights into the synergistic effect of doping and defect for simultaneously manipulating the light absorption and charge separation processes but also inspires further work to develop more efficient photocatalysts for H 2 O 2 production.
Background The novel coronavirus disease 2019 (COVID-19) has infected 1.9% of the world population by May 2, 2021. Since most previous studies that examined risk factors for mortality and severity were based on hospitalized individuals, population-based cohort studies are called for to provide evidence that can be extrapolated to the general population. Therefore, we aimed to examine the associations of comorbidities with mortality and disease severity in individuals with COVID-19 diagnosed in 2020 in Ontario, Canada. Methods and findings We conducted a retrospective cohort study of all individuals with COVID-19 in Ontario, Canada diagnosed between January 15 and December 31, 2020. Cases were linked to health administrative databases maintained in the ICES which covers all residents in Ontario. The primary outcome is all-cause 30-day mortality after the first COVID-19 diagnosis, and the secondary outcome is a composite severity index containing death and hospitalization. To examine the risk factors for the outcomes, we employed Cox proportional hazards regression models and logistic regression models to adjust for demographic, socio-economic variables and comorbidities. Results were also stratified by age groups. A total of 167,500 individuals were diagnosed of COVID-19 in 2020 and included in the study. About half (43.8%, n = 73,378) had at least one comorbidity. The median follow-up period were 30 days. The most common comorbidities were hypertension (24%, n = 40,154), asthma (16%, n = 26,814), and diabetes (14.7%, n = 24,662). Individuals with comorbidity had higher risk of mortality compared to those without (HR = 2.80, 95%CI 2.35–3.34; p<0.001), and the risk substantially was elevated from 2.14 (95%CI 1.76–2.60) to 4.81 (95%CI 3.95–5.85) times as the number of comorbidities increased from one to five or more. Significant predictors for mortality included comorbidities such as solid organ transplant (HR = 3.06, 95%CI 2.03–4.63; p<0.001), dementia (HR = 1.46, 95%CI 1.35–1.58; p<0.001), chronic kidney disease (HR = 1.45, 95%CI 1.34–1.57; p<0.001), severe mental illness (HR = 1.42, 95%CI%, 1.12–1.80; p<0.001), cardiovascular disease (CVD) (HR = 1.22, 95%CI, 1.15–1.30), diabetes (HR = 1.19, 95%, 1.12–1.26; p<0.001), chronic obstructive pulmonary disease (COPD) (HR = 1.19, 95%CI 1.12–1.26; p<0.001), cancer (HR = 1.17, 95%CI, 1.09–1.27; p<0.001), hypertension (HR = 1.16, 95%CI, 1.07–1.26; p<0.001). Compared to their effect in older age groups, comorbidities were associated with higher risk of mortality and severity in individuals under 50 years old. Individuals with five or more comorbidities in the below 50 years age group had 395.44 (95%CI, 57.93–2699.44, p<0.001) times higher risk of mortality compared to those without. Limitations include that data were collected during 2020 when the new variants of concern were not predominant, and that the ICES databases do not contain detailed individual-level socioeconomic and racial variables. Conclusion We found that solid organ transplant, dementia, chronic kidney disease, severe mental illness, CVD, hypertension, COPD, cancer, diabetes, rheumatoid arthritis, HIV, and asthma were associated with mortality or severity. Our study highlights that the number of comorbidities was a strong risk factor for deaths and severe outcomes among younger individuals with COVID-19. Our findings suggest that in addition of prioritizing by age, vaccination priority groups should also include younger population with multiple comorbidities.
As a novel concept of responding to disease epidemics, Fangcang shelter hospitals were deployed to expand the health system's capacity and provide medical services for nonsevere COVID-19 patients during the outbreak in Wuhan. To give insights on patient management within Fangcang hospitals, we conducted a retrospective analysis to: 1) describe the characteristics of the patients admitted to Fangcang hospitals and 2) explore risk factors for longer length of stay (LOS). We enrolled 136 confirmed COVID-19 patients, including asymptomatic patients and those with mild symptoms, who were hospitalized in the Wuti Fangcang Hospital. 58 patients completed the treatment and discharged before 1 March 2020. After describing patients' demographic and clinical characteristics, exposure history, treatment received and time course of the disease, we conducted linear regression analysis to identify factors influencing LOS. We found that patients having fever before admission were hospitalized 3.5 days (95%CI 1.39 to 5.63, p = 0.002) longer than those without fever and that patients having bilateral pneumonia were hospitalized 3.4 days (95%CI 0.49 to 6.25, p = 0.023) longer than those with normal CT scan results. We also found weak evidence suggesting that patients with diabetes were hospitalized 3.2 days longer than those without diabetes (95%CI-0.2 to 6.56, p = 0.065). However, we observed no significant differences in LOS between symptomatic and asymptomatic patients and between patients who received treatment and those without treatment. Longer duration of hospitalization among non-severe COVID-19 patients is associated with having fever, bilateral pneumonia on CT scan and diabetes. However, being asymptomatic and using supportive medications at the early stage of infection do not have significant influences on LOS. Our study is a single-centered study with relatively small sample size. The findings provide evidence for predicting
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