The influence of COVID-19 pandemic on PM2.5 air quality in Northern Taiwan from Q1 2020 to Q2 2021.

The study aimed to investigate the PM2.5 variations in different periods of COVID-19 control measures in Northern Taiwan from Quarter 1 (Q1) 2020 to Quarter 2 (Q2) 2021. PM2.5 sources were classified based on long-range transport (LRT) or local pollution (LP) in three study periods: one China lockdown (P1), and two restrictions in Taiwan (P2 and P3). During P1 the average PM2.5 concentrations from LRT (LRT-PM2.5-P1) were higher at Fuguei background station by 27.9% and in the range of 4.9-24.3% at other inland stations compared to before P1. The PM2.5 from LRT/LP mix or pure LP (Mix/LP-PM2.5-P1) was also higher by 14.2-39.9%. This increase was due to higher secondary particle formation represented by the increase in secondary ions (SI) and organic matter in PM2.5-P1 with the largest proportion of 42.17% in PM2.5 from positive matrix factorization (PMF) analysis. A similar increasing trend of Mix/LP-PM2.5 was found in P2 when China was still locked down and Taiwan was under an early control period but the rapidly increasing infected cases were confirmed. The shift of transportation patterns from public to private to avoid virus infection explicated the high correlation of the increasing infected cases with the increasing PM2.5. In contrast, the decreasing trend of LP-PM2.5-P3 was observed in P3 with the PM2.5 biases of ∼45% at all the stations when China was not locked down but Taiwan implemented a semi-lockdown. The contribution of gasoline vehicle sources in PM2.5 was reduced from 20.3% before P3 to 10% in P3 by chemical signatures and source identification using PMF implying the strong impact of strict control measures on vehicle emissions. In summary, PM2.5 concentrations in Northern Taiwan were either increased (P1 and P2) or decreased (P3) during the COVID-19 pandemic depending on control measures, source patterns and meteorological conditions.

Thyroxine changes in COVID-19 pandemic: A systematic review and meta-analysis

Objective COVID-19 infection may affect thyroid function. However, changes in thyroid function in COVID-19 patients have not been well described. This systematic review and meta-analysis assess thyroxine levels in COVID-19 patients, compared with non-COVID-19 pneumonia and healthy cohorts during the COVID-19 epidemic. Methods A search was performed in English and Chinese databases from inception to August 1, 2022. The primary analysis assessed thyroid function in COVID-19 patients, comparing non-COVID-19 pneumonia and healthy cohorts. Secondary outcomes included different severity and prognoses of COVID-19 patients. Results A total of 5873 patients were enrolled in the study. The pooled estimates of TSH and FT3 were significantly lower in patients with COVID-19 and non-COVID-19 pneumonia than in the healthy cohort (P < 0.001), whereas FT4 were significantly higher (P < 0.001). Patients with the non-severe COVID-19 showed significant higher in TSH levels than the severe (I2 = 89.9%, P = 0.002) and FT3 (I2 = 91.9%, P < 0.001). Standard mean differences (SMD) of TSH, FT3, and FT4 levels of survivors and non-survivors were 0.29 (P= 0.006), 1.11 (P < 0.001), and 0.22 (P < 0.001). For ICU patients, the survivors had significantly higher FT4 (SMD=0.47, P=0.003) and FT3 (SMD=0.51, P=0.001) than non-survivors. Conclusions Compared with the healthy cohort, COVID-19 patients showed decreased TSH and FT3 and increased FT4, similar to non-COVID-19 pneumonia. Thyroid function changes were related to the severity of COVID-19. Thyroxine levels have clinical significance for prognosis evaluation, especially FT3.

BPOZ-2 is a negative regulator of the NLPR3 inflammasome contributing to SARS-CoV-2-induced hyperinflammation

Introduction Inflammation play important roles in the initiation and progression of acute lung injury (ALI), acute respiratory distress syndrome (ARDS), septic shock, clotting dysfunction, or even death associated with SARS-CoV-2 infection. However, the pathogenic mechanisms underlying SARS-CoV-2-induced hyperinflammation are still largely unknown. Methods The animal model of septic shock and ALI was established after LPS intraperitoneal injection or intratracheal instillation. Bone marrow-derived macrophages (BMDMs) from WT and BPOZ-2 KO mouse strains were harvested from the femurs and tibias of mice. Immunohistology staining, ELISA assay, coimmunoprecipitation, and immunoblot analysis were used to detect the histopathological changes of lung tissues and the expression of inflammatory factors and protein interaction. Results and conclusions We show a distinct mechanism by which the SARS-CoV-2 N (SARS-2-N) protein targets Bood POZ-containing gene type 2 (BPOZ-2), a scaffold protein for the E3 ubiquitin ligase Cullin 3 that we identified as a negative regulator of inflammatory responses, to promote NLRP3 inflammasome activation. We first demonstrated that BPOZ-2 knockout (BPOZ-2 KO) mice were more susceptible to lipopolysaccharide (LPS)-induced septic shock and ALI and showed increased serum IL-1β levels. In addition, BMDMs isolated from BPOZ-2 KO mice showed increased IL-1β production in response to NLRP3 stimuli. Mechanistically, BPOZ-2 interacted with NLRP3 and mediated its degradation by recruiting Cullin 3. In particular, the expression of BPOZ-2 was significantly reduced in lung tissues from mice infected with SARS-CoV-2 and in cells overexpressing SARS-2-N. Importantly, proinflammatory responses triggered by the SARS-2-N were significantly blocked by BPOZ-2 reintroduction. Thus, we concluded that BPOZ-2 is a negative regulator of the NLPR3 inflammasome that likely contributes to SARS-CoV-2-induced hyperinflammation.

A general urban spreading pattern of COVID-19 and its underlying mechanism

Currently, the global situation of COVID-19 is aggravating, pressingly calling for efficient control and prevention measures. Understanding the spreading pattern of COVID-19 has been widely recognized as a vital step for implementing non-pharmaceutical measures. Previous studies explained the differences in contagion rates due to the urban socio-political measures, while fine-grained geographic urban spreading pattern still remains an open issue. Here, we fill this gap by leveraging the trajectory data of 197,808 smartphone users (including 17,808 anonymous confirmed cases) in nine cities in China. We find a general spreading pattern in all cities: the spatial distribution of confirmed cases follows a power-law-like model and the spreading centroid human mobility is time-invariant. Moreover, we reveal that long average traveling distance results in a high growth rate of spreading radius and wide spatial diffusion of confirmed cases in the fine-grained geographic model. With such insight, we adopt the Kendall model to simulate the urban spreading of COVID-19 which can well fit the real spreading process. Our results unveil the underlying mechanism behind the spatial-temporal urban evolution of COVID-19, and can be used to evaluate the performance of mobility restriction policies implemented by many governments and to estimate the evolving spreading situation of COVID-19.

Utility of Point-of-Care Lung Ultrasound for Clinical Classification of COVID-19.

In this study, the utility of point-of-care lung ultrasound for clinical classification of coronavirus disease (COVID-19) was prospectively assessed. Twenty-seven adult patients with COVID-19 underwent bedside lung ultrasonography (LUS) examinations three times each within the first 2 wk of admission to the isolation ward. We divided the 81 exams into three groups (moderate, severe and critically ill). Lung scores were calculated as the sum of points. A rank sum test and bivariate correlation analysis were carried out to determine the correlation between LUS on admission and clinical classification of COVID-19. There were dramatic differences in LUS (p < 0.001) among the three groups, and LUS scores (r = 0.754) correlated positively with clinical severity (p < 0.01). In addition, moderate, severe and critically ill patients were more likely to have low (≤9), medium (9-15) and high scores (≥15), respectively. This study provides stratification criteria of LUS scores to assist in quantitatively evaluating COVID-19 patients.

Thyroxine changes in COVID-19 pandemic: A systematic review and meta-analysis.

Objective: COVID-19 infection may affect thyroid function. However, changes in thyroid function in COVID-19 patients have not been well described. This systematic review and meta-analysis assess thyroxine levels in COVID-19 patients, compared with non-COVID-19 pneumonia and healthy cohorts during the COVID-19 epidemic. Methods: A search was performed in English and Chinese databases from inception to August 1, 2022. The primary analysis assessed thyroid function in COVID-19 patients, comparing non-COVID-19 pneumonia and healthy cohorts. Secondary outcomes included different severity and prognoses of COVID-19 patients. Results: A total of 5873 patients were enrolled in the study. The pooled estimates of TSH and FT3 were significantly lower in patients with COVID-19 and non-COVID-19 pneumonia than in the healthy cohort (P < 0.001), whereas FT4 were significantly higher (P < 0.001). Patients with the non-severe COVID-19 showed significant higher in TSH levels than the severe (I2 = 89.9%, P = 0.002) and FT3 (I2 = 91.9%, P < 0.001). Standard mean differences (SMD) of TSH, FT3, and FT4 levels of survivors and non-survivors were 0.29 (P= 0.006), 1.11 (P < 0.001), and 0.22 (P < 0.001). For ICU patients, the survivors had significantly higher FT4 (SMD=0.47, P=0.003) and FT3 (SMD=0.51, P=0.001) than non-survivors. Conclusions: Compared with the healthy cohort, COVID-19 patients showed decreased TSH and FT3 and increased FT4, similar to non-COVID-19 pneumonia. Thyroid function changes were related to the severity of COVID-19. Thyroxine levels have clinical significance for prognosis evaluation, especially FT3.

BPOZ-2 is a negative regulator of the NLPR3 inflammasome contributing to SARS-CoV-2-induced hyperinflammation.

Introduction: Inflammation play important roles in the initiation and progression of acute lung injury (ALI), acute respiratory distress syndrome (ARDS), septic shock, clotting dysfunction, or even death associated with SARS-CoV-2 infection. However, the pathogenic mechanisms underlying SARS-CoV-2-induced hyperinflammation are still largely unknown. Methods: The animal model of septic shock and ALI was established after LPS intraperitoneal injection or intratracheal instillation. Bone marrow-derived macrophages (BMDMs) from WT and BPOZ-2 KO mouse strains were harvested from the femurs and tibias of mice. Immunohistology staining, ELISA assay, coimmunoprecipitation, and immunoblot analysis were used to detect the histopathological changes of lung tissues and the expression of inflammatory factors and protein interaction. Results and conclusions: We show a distinct mechanism by which the SARS-CoV-2 N (SARS-2-N) protein targets Bood POZ-containing gene type 2 (BPOZ-2), a scaffold protein for the E3 ubiquitin ligase Cullin 3 that we identified as a negative regulator of inflammatory responses, to promote NLRP3 inflammasome activation. We first demonstrated that BPOZ-2 knockout (BPOZ-2 KO) mice were more susceptible to lipopolysaccharide (LPS)-induced septic shock and ALI and showed increased serum IL-1ß levels. In addition, BMDMs isolated from BPOZ-2 KO mice showed increased IL-1ß production in response to NLRP3 stimuli. Mechanistically, BPOZ-2 interacted with NLRP3 and mediated its degradation by recruiting Cullin 3. In particular, the expression of BPOZ-2 was significantly reduced in lung tissues from mice infected with SARS-CoV-2 and in cells overexpressing SARS-2-N. Importantly, proinflammatory responses triggered by the SARS-2-N were significantly blocked by BPOZ-2 reintroduction. Thus, we concluded that BPOZ-2 is a negative regulator of the NLPR3 inflammasome that likely contributes to SARS-CoV-2-induced hyperinflammation.

A general urban spreading pattern of COVID-19 and its underlying mechanism

Currently, the global situation of COVID-19 is aggravating, pressingly calling for efficient control and prevention measures. Understanding the spreading pattern of COVID-19 has been widely recognized as a vital step for implementing non-pharmaceutical measures. Previous studies explained the differences in contagion rates due to the urban socio-political measures, while fine-grained geographic urban spreading pattern still remains an open issue. Here, we fill this gap by leveraging the trajectory data of 197,808 smartphone users (including 17,808 anonymous confirmed cases) in nine cities in China. We find a general spreading pattern in all cities: the spatial distribution of confirmed cases follows a power-law-like model and the spreading centroid human mobility is time-invariant. Moreover, we reveal that long average traveling distance results in a high growth rate of spreading radius and wide spatial diffusion of confirmed cases in the fine-grained geographic model. With such insight, we adopt the Kendall model to simulate the urban spreading of COVID-19 which can well fit the real spreading process. Our results unveil the underlying mechanism behind the spatial-temporal urban evolution of COVID-19, and can be used to evaluate the performance of mobility restriction policies implemented by many governments and to estimate the evolving spreading situation of COVID-19.

COVID-19 epidemic and public health interventions in Shanghai, China: Statistical analysis of transmission, correlation and conversion

Background The Shanghai COVID-19 epidemic is an important example of a local outbreak and of the implementation of normalized prevention and disease control strategies. The precise impact of public health interventions on epidemic prevention and control is unknown. Methods We collected information on COVID-19 patients reported in Shanghai, China, from January 30 to May 31, 2022. These newly added cases were classified as local confirmed cases, local asymptomatic infections, imported confirmed cases and imported asymptomatic infections. We used polynomial fitting correlation analysis and illustrated the time lag plot in the correlation analysis of local and imported cases. Analyzing the conversion of asymptomatic infections to confirmed cases, we proposed a new measure of the conversion rate (Cr). In the evolution of epidemic transmission and the analysis of intervention effects, we calculated the effective reproduction number (Rt). Additionally, we used simulated predictions of public health interventions in transmission, correlation, and conversion analyses. Results (1) The overall level of Rt in the first three stages was higher than the epidemic threshold. After the implementation of public health intervention measures in the third stage, Rt decreased rapidly, and the overall Rt level in the last three stages was lower than the epidemic threshold. The longer the public health interventions were delayed, the more cases that were expected and the later the epidemic was expected to end. (2) In the correlation analysis, the outbreak in Shanghai was characterized by double peaks. (3) In the conversion analysis, when the incubation period was short (3 or 7 days), the conversion rate fluctuated smoothly and did not reflect the effect of the intervention. When the incubation period was extended (10 and 14 days), the conversion rate fluctuated in each period, being higher in the first five stages and lower in the sixth stage. Conclusion Effective public health interventions helped slow the spread of COVID-19 in Shanghai, shorten the outbreak duration, and protect the healthcare system from stress. Our research can serve as a positive guideline for addressing infectious disease prevention and control in China and other countries and regions.

External Supports Are Associated With the COVID-19 Vaccination in Chinese Breast Cancer Patients: A Cross-Sectional Survey.

Background: Coronavirus disease 2019 (COVID-19) is a global pandemic. Breast cancer is the most commonly diagnosed malignant cancer in China. Considering the specific national conditions, no evidence is available for factors associated with COVID-19 vaccination in patients with breast cancer. Methods: This was a cross-sectional survey, fielded from June 21 through June 27, 2021. A total of 944 nationally representative samples of Chinese breast cancer patients participating in the survey were included. Participant surveys included questions addressing who finished COVID-19 vaccination with the question "Have you taken the COVID-19 vaccine?", and response options were "Yes" and "No". Results: Overall, 730 (77.33%) women with breast cancer were unvaccinated, and only 214 (22.67%) were vaccinated with the COVID-19 vaccine. After adjusting for potential confounders, including both sociodemographic and clinical characteristics, we found that external support, including positive doctor suggestions (odds ratio (OR): 5.52; 95% confidence interval (CI): 3.50 - 8.71; P < 0.0001), positive support from surrounding people (OR: 11.65; 95% CI: 7.57 - 17.91; P < 0.0001), and negative initiative from the community (OR: 0.15; 95% CI: 0.06 - 0.35; P < 0.0001), was associated with COVID-19 vaccination rates among breast cancer patients. These results remain stable in subgroup analyses. We found that most participants (82.52%) understood the necessity of COVID-19 vaccinations in China was strong; however, the recognition regarding the COVID-19 vaccine showed different patterns between vaccinated and unvaccinated participants. Conclusions: Our findings suggest external support, including vaccination suggestions from surgeons or oncologists, vaccination suggestions from associated people, and residents' committee mandated vaccinations, was associated with the COVID-19 vaccination rates. Interventions regarding these factors and improving publicity as well as education regarding COVID-19 vaccines among breast cancer patients are warranted.

Use of temporal contact graphs to understand the evolution of COVID-19 through contact tracing data.

Digital contact tracing has been recently advocated by China and many countries as part of digital prevention measures on COVID-19. Controversies have been raised about their effectiveness in practice as it remains open how they can be fully utilized to control COVID-19. In this article, we show that an abundance of information can be extracted from digital contact tracing for COVID-19 prevention and control. Specifically, we construct a temporal contact graph that quantifies the daily contacts between infectious and susceptible individuals by exploiting a large volume of location-related data contributed by 10,527,737 smartphone users in Wuhan, China. The temporal contact graph reveals five time-varying indicators can accurately capture actual contact trends at population level, demonstrating that travel restrictions (e.g., city lockdown) in Wuhan played an important role in containing COVID-19. We reveal a strong correlation between the contacts level and the epidemic size, and estimate several significant epidemiological parameters (e.g., serial interval). We also show that user participation rate exerts higher influence on situation evaluation than user upload rate does, indicating a sub-sampled dataset would be as good at prediction. At individual level, however, the temporal contact graph plays a limited role, since the behavior distinction between the infected and uninfected individuals are not substantial. The revealed results can tell the effectiveness of digital contact tracing against COVID-19, providing guidelines for governments to implement interventions using information technology.

Risk spillovers in global financial markets: Evidence from the COVID-19 crisis

This paper aims to comprehensively investigate the dynamics of short-, medium- and long-term risk spillovers across the major financial markets in the context of COVID-19. Our main empirical findings are as follows. First, we find that the deterioration of the COVID-19 pandemic raised the risk of stock, bond, crude oil, and foreign exchange markets sequentially in the short term. Second, from the perspective of the medium and long term, the COVID-19 pandemic triggered substantial risk spillovers across financial markets, which is also highly correlated with the degree of investor panic. Third, we show that different markets played different roles in terms of risk transmission during the pandemic. Specifically, the stock and crude oil markets acted more as risk senders, the gold and foreign exchange markets acted more as risk receivers, and the bond market served as a transfer station of risk. Finally, we find that containment and health responses can effectively mitigate risk spillovers across markets in the short term, while expansionary fiscal policy can reduce them more effectively in the medium and long term. Our findings have important implications for policymakers and investors who aim to mitigate the adverse impact of the COVID-19 pandemic on financial markets.

Clinical Performance of Rapid Antigen Tests for the Detection of SARS-CoV-2 Infection in the Emergency Department and Community: A Retrospective Study.

Background: Rapid antigen tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection have been authorized for emergency use (EUA); however, the performance has not been fully evaluated in clinical contexts. This study aimed to provide evidence regarding the diagnostic performance of SARS-CoV-2 rapid antigen tests compared with the real-time reverse transcription-polymerase chain reaction (RT-PCR) test in the emergency department (ED) and community. Methods: Patients who underwent SARS-CoV-2 rapid antigen tests using the VTRUST COVID-19 Antigen Rapid Test (TD-4531) and real-time RT-PCR on the same day in the ED or community from May 24, 2021, to June 24, 2021, were examined. Results: Paired nasopharyngeal swabs were collected from 4022 suspected COVID-19 patients: 800 in the ED and 3222 in the community. Overall, 62 (1.54%) tested positive, 13 tested indeterminate, and 3947 tested negative by real-time RT-PCR. The sensitivity and specificity of the antigen test were 51.61% and 99.44% (overall), 62.50% and 99.61% (ED), and 31.82% and 99.40% (community), respectively. There were 30 false negatives and 22 false positives. Among the false negatives, 16.67% had a cycle threshold (Ct) value of <25. Conclusion: The VTRUST COVID-19 Antigen Rapid Test showed comparable specificity as real-time RT-PCR for the ED and community, but the sensitivity was relatively low, especially when the Ct value was >25. This test can be useful for the rapid identification of infected subjects in an epidemic situation.

Effectiveness of the talent cultivation training program for industry transformation in Taiwan during the COVID-19 pandemic

In response to the impact of the COVID-19 pandemic on the Taiwanese tourism and hospitality industry, the Taiwanese government launched an industry revival and revitalization project. Subsidies were given for cultivating talent and industry transformation. The industry implemented talent cultivation courses to improve the skills and knowledge of workers and facilitate financial subsidization. This study reviewed the talent cultivation subsidy and training results for employees participating in training programs within Taiwan’s lodging industry. The results showed that the government promoted large-scale industry transformation and talent cultivation, and industry employees who received the training responded to it positively.

The Well-Being of the German Adult Population Measured with the WHO-5 over Different Phases of the COVID-19 Pandemic: An Analysis within the COVID-19 Snapshot Monitoring Study (COSMO).

The aim of this study is to evaluate factors associated with the subjective well-being (SWB) and suspected depression measured with WHO-5 among German adults during different phases of the COVID-19 pandemic. Survey data were analyzed from the COVID-19 Snapshot Monitoring (COSMO) study, which collected data from 972, 1013, and 973 participants in time point 1 (19-20 May 2020), time point 2 (15-16 September 2020), and time point 3 (21-22 December 2020), respectively. Descriptive analyses and logistic regression analyses to identify the factors associated with suspected depression (WHO-5 ≤ 50) were conducted. Data showed that the mean WHO-5 scores in three time points were 56.17, 57.27, and 53.93, respectively. The risk of suspected depression was increased by about 1.5 times for females, 2.5-3 times among 18-24 year-olds compared to ages above 65 years, 1.5 times for singles, 2 times for those with chronic illnesses, and 2-3 times for people living in poverty. The main study findings show that German adult SWB is lower than pre-pandemic reference values. Special focus should be placed on vulnerable groups, such as females, younger persons, and people living in poverty who are most prone to a reduction in SWB and therefore suspected depression.

The risk spillover effect of the COVID-19 pandemic on energy sector: Evidence from China

Detecting the adverse effects of major emergencies on financial markets and real economy is of great importance not only for short-term policy reactions but also for economic and financial stability. This is the lesson we learnt from the COVID-19 pandemic. This paper focuses on the risk spillover effect of the COVID-19 on Chinese energy industry using a high-dimensional and time-varying factor-augmented VAR model. The results show that the net volatility spillovers of the pandemic remain positive to all underlying energy sectors during January to June of 2020 and February to April of 2021. For the former sub-period, the volatility spillover of the COVID-19 is not only the highest, but also lasts longest for oil exploitation sector, followed by the power and gas sectors. While for the latter sub-period, the COVID-19 has relatively higher volatility spillovers to the power, coal mining and petrochemical sectors. These findings suggest that the COVID-19 has significant risk spillover effects on Chinese energy sectors, and the effects vary among different energy sub-sectors and across different periods of time.

SARS-CoV-2 Variants, RBD Mutations, Binding Affinity, and Antibody Escape.

Since 2020, the receptor-binding domain (RBD) of the spike protein of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been constantly mutating, producing most of the notable missense mutations in the context of "variants of concern", probably in response to the vaccine-driven alteration of immune profiles of the human population. The Delta variant, in particular, has become the most prevalent variant of the epidemic, and it is spreading in countries with the highest vaccination rates, causing the world to face the risk of a new wave of the contagion. Understanding the physical mechanism responsible for the mutation-induced changes in the RBD's binding affinity, its transmissibility, and its capacity to escape vaccine-induced immunity is the "urgent challenge" in the development of preventive measures, vaccines, and therapeutic antibodies against the coronavirus disease 2019 (COVID-19) pandemic. In this study, entropy-enthalpy compensation and the Gibbs free energy change were used to analyze the impact of the RBD mutations on the binding affinity of SARS-CoV-2 variants with the receptor angiotensin converting enzyme 2 (ACE2) and existing antibodies. Through the analysis, we found that the existing mutations have already covered almost all possible detrimental mutations that could result in an increase of transmissibility, and that a possible mutation in amino-acid position 498 of the RBD can potentially enhance its binding affinity. A new calculation method for the binding energies of protein-protein complexes is proposed based on the entropy-enthalpy compensation rule. All known structures of RBD-antibody complexes and the RBD-ACE2 complex comply with the entropy-enthalpy compensation rule in providing the driving force behind the spontaneous protein-protein docking. The variant-induced risk of breakthrough infections in vaccinated people is attributed to the L452R mutation's reduction of the binding affinity of many antibodies. Mutations reversing the hydrophobic or hydrophilic performance of residues in the spike RBD potentially cause breakthrough infections of coronaviruses due to the changes in geometric complementarity in the entropy-enthalpy compensations between antibodies and the virus at the binding sites.

An optimization model for planning testing and control strategies to limit the spread of a pandemic - The case of COVID-19.

The global health crisis caused by the coronavirus SARS-CoV-2 has highlighted the importance of efficient disease detection and control strategies for minimizing the number of infections and deaths in the population and halting the spread of the pandemic. Countries have shown different preparedness levels for promptly implementing disease detection strategies, via mass testing and isolation of identified cases, which led to a largely varying impact of the outbreak on the populations and health-care systems. In this paper, we propose a new pandemic resource allocation model for allocating limited disease detection and control resources, in particular testing capacities, in order to limit the spread of a pandemic. The proposed model is a novel epidemiological compartmental model formulated as a non-linear programming model that is suitable to address the inherent non-linearity of an infectious disease progression within the population. A number of novel features are implemented in the model to take into account important disease characteristics, such as asymptomatic infection and the distinct risk levels of infection within different segments of the population. Moreover, a method is proposed to estimate the vulnerability level of the different communities impacted by the pandemic and to explicitly consider equity in the resource allocation problem. The model is validated against real data for a case study of COVID-19 outbreak in France and our results provide various insights on the optimal testing intervention time and level, and the impact of the optimal allocation of testing resources on the spread of the disease among regions. The results confirm the significance of the proposed modeling framework for informing policymakers on the best preparedness strategies against future infectious disease outbreaks.

A macrophage-targeted platform for extending drug dosing with polymer prodrugs for pulmonary infection prophylaxis.

Pulmonary melioidosis is a bacterial disease with high morbidity and a mortality rate that can be as high as 40% in resource-poor regions of South Asia. This disease burden is linked to the pathogen's intrinsic antibiotic resistance and protected intracellular localization in alveolar macrophages. Current treatment regimens require several antibiotics with multi-month oral and intravenous administrations that are difficult to implement in under-resourced settings. Herein, we report that a macrophage-targeted polyciprofloxacin prodrug acts as a surprisingly effective pre-exposure prophylactic in highly lethal murine models of aerosolized human pulmonary melioidosis. A single dose of the polymeric prodrug maintained high lung drug levels and targeted an intracellular depot of ciprofloxacin to the alveolar macrophage compartment that was sustained over a period of 7 days above minimal inhibitory concentrations. This intracellular pharmacokinetic profile provided complete pre-exposure protection in a BSL-3 model with an aerosolized clinical isolate of Burkholderia pseudomallei from Thailand. This total protection was achieved despite the bacteria's relative resistance to ciprofloxacin and where an equivalent dose of pulmonary-administered ciprofloxacin was ineffective. For the first time, we demonstrate that targeting the intracellular macrophage compartment with extended antibiotic dosing can achieve pre-exposure prophylaxis in a model of pulmonary melioidosis. This fully synthetic and modular therapeutic platform could be an important therapeutic approach with new or re-purposed antibiotics for melioidosis prevention and treatment, especially as portable inhalation devices in high-risk, resource-poor settings.