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1.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-322732

ABSTRACT

In epidemiology, the effective reproduction number $R_e$ is used to characterize the growth rate of an epidemic outbreak. In this paper, we investigate properties of $R_e$ for a modified SEIR model of COVID-19 in the city of Houston, TX USA, in which the population is divided into low-risk and high-risk subpopulations. The response of $R_e$ to two types of control measures (testing and distancing) applied to the two different subpopulations is characterized. A nonlinear cost model is used for control measures, to include the effects of diminishing returns. We propose three types of heuristic strategies for mitigating COVID-19 that are targeted at reducing $R_e$, and we exhibit the tradeoffs between strategy implementation costs and number of deaths. We also consider two variants of each type of strategy: basic strategies, which consider only the effects of controls on $R_e$, without regard to subpopulation;and high-risk prioritizing strategies, which maximize control of the high-risk subpopulation. Results showed that of the three heuristic strategy types, the most cost-effective involved setting a target value for $R_e$ and applying sufficient controls to attain that target value. This heuristic led to strategies that begin with strict distancing of the entire population, later followed by increased testing. Strategies that maximize control on high-risk individuals were less cost-effective than basic strategies that emphasize reduction of the rate of spreading of the disease. The model shows that delaying the start of control measures past a certain point greatly worsens strategy outcomes. We conclude that the effective reproduction can be a valuable real-time indicator in determining cost-effective control strategies.

2.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-311356

ABSTRACT

On July 30 the COVID-19 pandemic expanded to over 17 million cases and over 660 thousand deaths worldwide (Dong et al., 2020). High-risk populations include people older than 65 years, with comorbidities such as hypertension, diabetes, chronic pulmonary disease, and immunocompromised patients (Sokolowska et al., 2020). Primary immunodeficient patients have been identified as a high-risk population for infectious diseases including viral infections (Sokolowska et al., 2020) and severe COVID-19 (Wang et al., 2020). However, the SARS-CoV-2 infection and the course of the disease in these patients is not well known (Gao et al., 2020;Shaker et al., 2020). The impact of tailored healthcare on these patients for COVID-19 has not been stablished (Waltuch et al., 2020;Zhong et al., 2020). Although immunoglobulin replacement protects them against various types of infections, its role against COVID-19 is not guaranteed (Waltuch et al., 2020) because of the lack of SARS-CoV-2 specific antibodies (Sanders et al., 2020). Furthermore, it remains unclear if immunomodulation could play a role in immunodeficient patients (Waltuch et al., 2020;Zhong et al., 2020) or in multisystem inflammatory syndrome in children (MIS-C) (Waltuch et al., 2020;Yáñez et al., 2020b). The COVID-19 pandemic burden has called for urgent therapeutic solutions in treating infected patients (Sanders et al., 2020). However, its poorly understood pathophysiological process remains a therapeutic challenge, especially in high risk populations as primary immunodeficiency patients (Sanders et al., 2020). Various specific and unspecific targets for SARS-CoV-2 are currently been evaluated in various preclinical and clinical studies. Some of the relevant targets include anti IL-6R antibodies, IL-1 R antagonists, JAK-STAT inhibitors, CD147 antibodies, convalescent plasma, eculizumab targeting complement C5, immunomodulators and anti-inflammatory drugs (Sanders et al., 2020). However, the inclusion of primary immunodeficiency patients is not part of the drug development paradigm. Colchicine is a drug used in various auto-inflammatory disorders such as Familiar Mediterranean Fever and Bechet disease (Maggiore and Manenti, 2020) that have a close correlation with primary immunodeficiency (Savic et al., 2020). The mechanism of action of colchicine is based on counteracting the assembly of the NLRP3 inflammasome and mitigating the interleukin activation (Deftereos et al., 2020) and potentially preventing the cytokine storm (Montealegre-Gómez et al., 2020) via presumably the viroporin E (Castaño-Rodriguez et al., 2018). Four (4) randomized clinical trials are in progress to assess colchicine efficacy in COVID-19 patients administered alone or in combination with Lopinavir/Ritonavir (Deftereos et al., 2020). However, these Phase 2 and Phase 3 clinical trials do not include primary immunodeficiency patients.Brazil is currently the second country in the world with the highest number of confirmed COVID-19 with over 2 million cases (Dong et al., 2020). Even though there is no clear data of the total burden of primary immunodeficient patients in Brazil, it is estimated that 160,000 cases can be accounted for (Carneiro-Sampaio et al., 2013). Challenges in clinical diagnosis and auxiliary methods for primary immunodeficiencies have historically been a problem, but also in the treatment of these patients in both the public and private sectors specially in Latin America (Costa-Carvalho et al., 2017). The latter has become more evident during the COVID-19 pandemic where special care protocols for patients with immunodeficiencies are needed. However, clinics currently are focused in performing PCR tests, blood testing for antibodies, CT-scans, and consultation visits of COVID-19 confirmed or suspected cases. Thus, an immunocompromised patient would not be able to go to a regular clinic nowadays because the risk would be too high (Shaker et al., 2020). Because of the deep concern in these patients, in our clinic in Brazil we have implemented telemedicine to monitor and continue their treatment. However, in-office consultations are still necessary to attend certain cases and because of this we have implemented strict in-office protocols. Our healthcare workers involved in the care of patients with immunodeficiencies must follow rules of behavior and social responsibility to avoid the spread of the virus. Furthermore, our healthcare workers undergo constant training to answer all their COVID-19 related concerns and provide psychological support when needed in order to avoid anxiety, distress and intention to change jobs (Yáñez et al., 2020a). We are also in the approval stage of a Phase 3 clinical trial in Brazil to evaluate effect of colchicine in COVID-19 patients (n=200). We are also in discussion with the Brazilian authorities to start a clinical trial that includes primary immunodeficient and COVID-19 concomitant patients in order to better understand the course of the disease in this population and assess potential immunomodulating treatments. The COVID-19 pandemic is a deep concern for the primary immunodeficient patients, we urge to re-evaluate their inclusion in COVID-19 clinical trials, and to pay closer attention to their proper care, treatment and monitoring in clinics. This is the right time to not overlook this neglected high-risk population in order to offer them opportune, secure and quality care.

3.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-311355

ABSTRACT

Peru has an underfunded and precarious healthcare system, which has reflected in a high number of physician deaths because of COVID-19. Insufficient and inadequate distribution of PPE to physicians have been identified as a main cause of physicians’ deaths during the COVID-19 pandemic. We illustrate the case of a physician in Peru using regular plastic bags as an improvised PPE in an effort to protect himself during the examination of a possible COVID-19 patient.

4.
J Intern Med ; 291(2): 232-240, 2022 02.
Article in English | MEDLINE | ID: covidwho-1455598

ABSTRACT

BACKGROUND: Anti-SARS-CoV-2 S antibodies prevent viral replication. Critically ill COVID-19 patients show viral material in plasma, associated with a dysregulated host response. If these antibodies influence survival and viral dissemination in ICU-COVID patients is unknown. PATIENTS/METHODS: We studied the impact of anti-SARS-CoV-2 S antibodies levels on survival, viral RNA-load in plasma, and N-antigenaemia in 92 COVID-19 patients over ICU admission. RESULTS: Frequency of N-antigenaemia was >2.5-fold higher in absence of antibodies. Antibodies correlated inversely with viral RNA-load in plasma, representing a protective factor against mortality (adjusted HR [CI 95%], p): (S IgM [AUC ≥ 60]: 0.44 [0.22; 0.88], 0.020); (S IgG [AUC ≥ 237]: 0.31 [0.16; 0.61], <0.001). Viral RNA-load in plasma and N-antigenaemia predicted increased mortality: (N1-viral load [≥2.156 copies/ml]: 2.25 [1.16; 4.36], 0.016); (N-antigenaemia: 2.45 [1.27; 4.69], 0.007). CONCLUSIONS: Low anti-SARS-CoV-2 S antibody levels predict mortality in critical COVID-19. Our findings support that these antibodies contribute to prevent systemic dissemination of SARS-CoV-2.


Subject(s)
Antibodies, Viral/blood , Antigens, Viral/blood , COVID-19 , COVID-19/immunology , COVID-19/mortality , Critical Illness , Humans , RNA, Viral/blood , SARS-CoV-2
5.
Mathematics ; 9(15):1777, 2021.
Article in English | MDPI | ID: covidwho-1335144

ABSTRACT

In this paper, we present a three-stage algorithm for finding numerical solutions for optimal control problems. The algorithm first performs an exhaustive search through a discrete set of widely dispersed solutions which are representative of large subregions of the search space;then, it uses the search results to initialize a Monte Carlo process that searches quasi-randomly for a best solution;then, it finally uses a Newton-type iteration to converge to a solution that satisfies mathematical conditions of local optimality. We demonstrate our methodology on an epidemiological model of the coronavirus disease with testing and distancing controls applied over a period of 180 days to two different subpopulations (low-risk and high-risk), where model parameters are chosen to fit the city of Houston, Texas, USA. In order to enable the user to select his/her preferred trade-off between (number of deaths) and (herd immunity) outcomes, the objective function includes costs for deaths and non-immunity. Optimal strategies are estimated for a grid of (death cost) × (non-immunity cost) combinations, in order to obtain a Pareto curve that represents optimum trade-offs. The levels of the four controls for the different Pareto-optimal solutions over the 180-day period are visually represented and their characteristics discussed. Three different variants of the algorithm are run in order to determine the relative importance of the three stages in the optimization. Results from the three algorithm variants are fairly consistent, indicating that solutions are robust. Results also show that the Monte Carlo stage plays an especially prominent role in the optimization, but that all three stages of the process make significant contributions towards finding lower-cost, more effective control strategies.

6.
J Math Ind ; 11(1): 11, 2021.
Article in English | MEDLINE | ID: covidwho-1286836

ABSTRACT

In epidemiology, the effective reproduction number R e is used to characterize the growth rate of an epidemic outbreak. If R e > 1 , the epidemic worsens, and if R e < 1 , then it subsides and eventually dies out. In this paper, we investigate properties of R e for a modified SEIR model of COVID-19 in the city of Houston, TX USA, in which the population is divided into low-risk and high-risk subpopulations. The response of R e to two types of control measures (testing and distancing) applied to the two different subpopulations is characterized. A nonlinear cost model is used for control measures, to include the effects of diminishing returns. Lowest-cost control combinations for reducing instantaneous R e to a given value are computed. We propose three types of heuristic strategies for mitigating COVID-19 that are targeted at reducing R e , and we exhibit the tradeoffs between strategy implementation costs and number of deaths. We also consider two variants of each type of strategy: basic strategies, which consider only the effects of controls on R e , without regard to subpopulation; and high-risk prioritizing strategies, which maximize control of the high-risk subpopulation. Results showed that of the three heuristic strategy types, the most cost-effective involved setting a target value for R e and applying sufficient controls to attain that target value. This heuristic led to strategies that begin with strict distancing of the entire population, later followed by increased testing. Strategies that maximize control on high-risk individuals were less cost-effective than basic strategies that emphasize reduction of the rate of spreading of the disease. The model shows that delaying the start of control measures past a certain point greatly worsens strategy outcomes. We conclude that the effective reproduction can be a valuable real-time indicator in determining cost-effective control strategies.

7.
Transl Res ; 236: 147-159, 2021 10.
Article in English | MEDLINE | ID: covidwho-1243239

ABSTRACT

We aimed to examine the circulating microRNA (miRNA) profile of hospitalized COVID-19 patients and evaluate its potential as a source of biomarkers for the management of the disease. This was an observational and multicenter study that included 84 patients with a positive nasopharyngeal swab Polymerase chain reaction (PCR) test for SARS-CoV-2 recruited during the first pandemic wave in Spain (March-June 2020). Patients were stratified according to disease severity: hospitalized patients admitted to the clinical wards without requiring critical care and patients admitted to the intensive care unit (ICU). An additional study was completed including ICU nonsurvivors and survivors. Plasma miRNA profiling was performed using reverse transcription polymerase quantitative chain reaction (RT-qPCR). Predictive models were constructed using least absolute shrinkage and selection operator (LASSO) regression. Ten circulating miRNAs were dysregulated in ICU patients compared to ward patients. LASSO analysis identified a signature of three miRNAs (miR-148a-3p, miR-451a and miR-486-5p) that distinguishes between ICU and ward patients [AUC (95% CI) = 0.89 (0.81-0.97)]. Among critically ill patients, six miRNAs were downregulated between nonsurvivors and survivors. A signature based on two miRNAs (miR-192-5p and miR-323a-3p) differentiated ICU nonsurvivors from survivors [AUC (95% CI) = 0.80 (0.64-0.96)]. The discriminatory potential of the signature was higher than that observed for laboratory parameters such as leukocyte counts, C-reactive protein (CRP) or D-dimer [maximum AUC (95% CI) for these variables = 0.73 (0.55-0.92)]. miRNA levels were correlated with the duration of ICU stay. Specific circulating miRNA profiles are associated with the severity of COVID-19. Plasma miRNA signatures emerge as a novel tool to assist in the early prediction of vital status deterioration among ICU patients.


Subject(s)
COVID-19/blood , COVID-19/genetics , Circulating MicroRNA/blood , Hospitalization , Severity of Illness Index , Aged , Biomarkers/blood , COVID-19/virology , Critical Illness , Female , Humans , Intensive Care Units , Male , SARS-CoV-2/physiology
8.
Crit Care ; 24(1): 691, 2020 12 14.
Article in English | MEDLINE | ID: covidwho-977684

ABSTRACT

BACKGROUND: COVID-19 can course with respiratory and extrapulmonary disease. SARS-CoV-2 RNA is detected in respiratory samples but also in blood, stool and urine. Severe COVID-19 is characterized by a dysregulated host response to this virus. We studied whether viral RNAemia or viral RNA load in plasma is associated with severe COVID-19 and also to this dysregulated response. METHODS: A total of 250 patients with COVID-19 were recruited (50 outpatients, 100 hospitalized ward patients and 100 critically ill). Viral RNA detection and quantification in plasma was performed using droplet digital PCR, targeting the N1 and N2 regions of the SARS-CoV-2 nucleoprotein gene. The association between SARS-CoV-2 RNAemia and viral RNA load in plasma with severity was evaluated by multivariate logistic regression. Correlations between viral RNA load and biomarkers evidencing dysregulation of host response were evaluated by calculating the Spearman correlation coefficients. RESULTS: The frequency of viral RNAemia was higher in the critically ill patients (78%) compared to ward patients (27%) and outpatients (2%) (p < 0.001). Critical patients had higher viral RNA loads in plasma than non-critically ill patients, with non-survivors showing the highest values. When outpatients and ward patients were compared, viral RNAemia did not show significant associations in the multivariate analysis. In contrast, when ward patients were compared with ICU patients, both viral RNAemia and viral RNA load in plasma were associated with critical illness (OR [CI 95%], p): RNAemia (3.92 [1.183-12.968], 0.025), viral RNA load (N1) (1.962 [1.244-3.096], 0.004); viral RNA load (N2) (2.229 [1.382-3.595], 0.001). Viral RNA load in plasma correlated with higher levels of chemokines (CXCL10, CCL2), biomarkers indicative of a systemic inflammatory response (IL-6, CRP, ferritin), activation of NK cells (IL-15), endothelial dysfunction (VCAM-1, angiopoietin-2, ICAM-1), coagulation activation (D-Dimer and INR), tissue damage (LDH, GPT), neutrophil response (neutrophils counts, myeloperoxidase, GM-CSF) and immunodepression (PD-L1, IL-10, lymphopenia and monocytopenia). CONCLUSIONS: SARS-CoV-2 RNAemia and viral RNA load in plasma are associated with critical illness in COVID-19. Viral RNA load in plasma correlates with key signatures of dysregulated host responses, suggesting a major role of uncontrolled viral replication in the pathogenesis of this disease.


Subject(s)
COVID-19/complications , RNA, Viral/analysis , Viral Load/immunology , Adult , Aged , Biomarkers/analysis , Biomarkers/blood , COVID-19/blood , Chi-Square Distribution , Critical Illness , Female , Humans , Male , Middle Aged , Multivariate Analysis , Polymerase Chain Reaction/methods , RNA, Viral/blood , Statistics, Nonparametric
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