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IntroductionSars-CoV-2 (severe acute respiratory syndrome coronavirus-2) is an RNA virus that causes Covid-19 disease. This disease started in the city of Wuhan in China. This is not the first time that the coronavirus has caused an outbreak, in the last twenty years the coronavirus SARS-CoV (Severe Acute Respiratory Syndrome coronavirus) and MERSCoV (Middle East Respiratory Syndrome coronavirus) have caused two major outbreaks. The main structure of SARS-CoV-2 is built from membrane (M), envelope (E), nucleocapsid (N) and spike (S). When the body is infected by the virus, the virus enters the host cells by binding to the ACE2 receptor. Once the virus has entered the cell, it releases viral RNA. The virus's particles multiply inside the cell. New virus particles from the infected cell are produced, which in its turn infect new cells. The immune system against SARS-CoV-2 involves both the cellular and humoral arms, with neutralizing antibodies directed primarily against the S antigen.ObjectivesThis research aimed to study the litteratur describing how long the antibodies and memory cells remain in the blood, and how long the protection against the virus lasts.MethodThis work was based on six scientific articles to answer the question: How long protective antibody levels last in the plasma after resolution of a Covid-19 infection? To answer the question, the levels of the antibodies of different classes, IgG, IgM and IgA, against the receptorbinding domain (RBD)/ S, N protein were analysed as reported in litterature, as well as the reported amounts of T memory cells and B memory cells.ResultsHumans produce SARS-CoV-2-specific antibodies, especially IgM and IgG antibodies, and T cells response to SARS-CoV-2 infection. IgG and IgM antibody levels were higher in patients whith severe Covid-19 than in mild cases. Studies cohort included patients from 18 to 90 years old. The studies lasted on from three months and up to one year.

Contexte : Partout dans le monde, la population âgée en hébergement a été la plus lourdement affectée par la pandémie de COVID-19, du point de vue des infections et des décès. Or, ces mêmes personnes ont été exclues d’une grande partie de la littérature scientifique. Ce mémoire décrit l’évolution des éclosions dans 17 CHSLD publics de Montréal, dont certains ont été fortement atteints alors que d’autres ont été épargnés pendant la première vague (23 février au 11 juillet 2020), en cherchant à élucider les facteurs associés à l’incidence et à la létalité de la COVID-19. Méthodes : Des données institutionnelles ont été recueillies sur les 17 CHSLD du CIUSSS Centre-Sud-de-l'Île-de-Montréal et des données individuelles ont été obtenues grâce à une révision des 1197 dossiers de patients atteints de la COVID-19 en première vague. Dans l’analyse ARIMA, des séries chronologiques ont été construites pour les cas incidents bruts chez les résidents en CHSLD et dans la ville de Montréal, afin d’évaluer l’impact de deux interventions, soit le port généralisé du masque de procédure et le dépistage élargi des résidents et des employés. Dans l’analyse des infections par CHSLD, des modèles de régression de type binomial négatif ont été construits pour estimer l’effet des facteurs de risque institutionnels sur l’incidence de la COVID-19 chez les résidents. Dans l’analyse de surmortalité, les excès de décès durant la période de février à juillet ont été évalués avec des tests t et des ratios de taux entre l’année 2020 et la moyenne des quatre années précédentes (2016-2019). Enfin, pour l’analyse de mortalité dans la cohorte rétrospective de résidents atteints de la COVID-19, des modèles de régression logistique à effets mixtes ont été utilisés pour évaluer les facteurs institutionnels et les traitements associés à la mortalité dans les 30 jours suivant un diagnostic de COVID-19, en contrôlant pour les facteurs de risque individuels. Résultats : Dans l’analyse de série chronologique ARIMA, chaque augmentation d’un cas incident quotidien par 100 000 à Montréal était associée avec une augmentation de 0,051 (IC95% 0,044 à 0,058) fois l’incidence quotidienne en CHSLD la semaine suivante, chez les résidents à risque. De plus, en contrôlant pour la transmission communautaire, chaque palier d’intensification du dépistage était associé à une diminution de l’incidence de 11,8 fois (IC95% -15,1 à -8,5) dans les deux semaines suivantes, chez les résidents à risque. Dans le modèle explicatif des infections au niveau des CHSLD, la pénurie sévère d’infirmières auxiliaires (IRR 3,2; IC95% 1,4 à 7,2), la mauvaise performance aux audits ministériels (IRR 3,0; IC95% 1,1 à 7,8) et un score moyen d’autonomie plus faible (IRR 2,1; IC95% 1,4 à 3,1) étaient associés au taux d’incidence par centre. En revanche, la présence de zone chaude dédiée aux patients COVID-19 (IRR; 0,56 IC95% 0,34 à 0,92) était protectrice. Pour l’ensemble des 17 CHSLD avec 2670 lits, l’excès de décès de février à juillet 2020 était de 428 (IC95% 409 à 447). Comparé aux quatre années précédentes, il y a eu plus que le double (IRR 2,3; IC95% 2,1 à 2,5) de décès en 2020 pendant la période de la première vague. Pour 12 CHSLD qui ont vécu des éclosions importantes, les excès de décès en 2020 variaient de 5,2 à 41,9 décès par 100 lits, avec une surmortalité par rapport aux années précédentes allant de 1,9 à 3,8. Selon l’analyse de mortalité dans la cohorte rétrospective, les facteurs individuels associés à la mortalité dans les 30 jours suivant le diagnostic de COVID-19 étaient l’âge (OR 1,58; IC95% 1,35 à 1,85 par tranche additionnelle de 10 ans), le sexe masculin (OR 2,37; IC95% 1,70 à 3,32), la perte d’autonomie (OR 1,12; IC95% 1,05 à 1,20 pour chaque augmentation d’un point à l’Iso-SMAF), le niveau d’intervention médicale C (OR 3,43; IC95% 1,57 à 7,51) et D (OR 3,61; IC95% 1,47 à 8,89) comparé au niveau A, ainsi que les diagnostics de trouble neurocognitif (OR 1,54; IC95% 1,04 à 2,29) et d’insuffisance cardiaque (OR 2,36; IC95% 1,45 à 3,85). Le traitement avec une thromboprophylaxie (OR 0,42; IC95% 0,29 à 0,63) et l’infection tardive après le 20 avril 2020 (OR 0,46; IC95% 0,33 à 0,65) étaient associés à la survie à 30 jours. Pour les facteurs institutionnels, la pénurie sévère de 25% ou plus d’infirmières auxiliaires (OR 1,91; IC95% 1,14 à 3,21 par rapport à une pénurie légère < 15%) et la taille du centre (OR 1,77; IC95% 1,17 à 2,68 pour chaque 100 lits additionnels) étaient associés au décès dans les 30 jours. Conclusion : Ce mémoire a relevé plusieurs facteurs de risque modifiables au niveau institutionnel associés aux infections et aux décès COVID-19, dont le dépistage, l’adhérence aux directives ministérielles de prévention et contrôle des infections, la pénurie d’infirmières auxiliaires et le nombre de lits par centre. Ces enjeux cruciaux devront être au cœur des futures orientations et politiques touchant les centres d’hébergement, pour cette pandémie et au-delà. / Background: In the midst of the COVID-19 pandemic, the population of long-term care residents has been the hardest hit by infections and deaths all around the world. Yet, these same individuals have been excluded from vast segments of the scientific literature. This thesis describes the evolution of outbreaks in 17 public long-term care facilities (“CHSLD”) in Montreal, some of which were severely affected and others were relatively spared during the first wave (February 23 to July 12, 2020), in search of risk factors associated with COVID-19 cases and deaths. Methods: Institutional-level data on the 17 CHSLDs were collected from relevant administrative departments within the establishment (CIUSSS Centre-Sud-de-l'Île-de-Montréal), and individual-level data was obtained from the chart reviews of 1,197 first wave COVID-19 patients. For the ARIMA analysis, time series were built using the crude incidence rates among CHSLD residents and in the city of Montreal, in order to assess the impact of two interventions – introduction of the mask-wearing policy and generalized testing among residents and staff. For the analysis of facility-level infection rates, negative binomial regression models were built to estimate the effects of several institutional risk factors on incident cases. As for the excess mortality analysis, excess death and relative mortality were estimated using one-sample t-tests and rate ratio tests to compare 2020 deaths with average deaths in the previous four years (2016-2019), for the period of February to July. Lastly, for the survival analysis of the retrospective cohort, mixed-effects logistic regression models were used to identify institutional factors and treatments associated with 30-day mortality after a COVID-19 diagnosis, while controlling for individual risk factors. Results: In the ARIMA time series analysis, each additional case per 100,000 per day in Montreal was associated with a 0.051 (95%CI 0.044 to 0.058) increase in CHSLD daily incidence a week later, among at-risk residents. In addition, while controlling for community transmission, increased testing intensity was associated with a 11.8 (95%CI -15.1 to -8.5) decrease in CHSLD daily incidence two weeks later, among at-risk residents. In the negative binomial regression model for facility-level COVID-19 infections, poor performance on ministry audits (IRR 3.0 95%CI 1.1 to 7.8), severe shortage of auxiliary nurses (IRR 3.2 95%CI 1.4 to 7.2) and lower average autonomy scores (IRR 2.1 95%CI 1.4 to 3.1) were associated with incident cases, while the presence of a COVID-19 unit or “red zone” (IRR 0.56 95%CI 0.34 to 0.92) was inversely associated with infections. For the 17 CHSLDs, excess deaths from February to July 2020 was 428 (95%CI 409 to 447). Compared to the same period in the previous four years, 2020 mortality during the first wave was 2.3 (IRR 95%CI 2.1 to 2.5) times higher. For a subset of 12 facilities that experienced substantial outbreaks, excess deaths in 2020 varied from 5.2 to 41.9 deaths per 100 beds, with significant excess mortality between 1.9 and 3.8, relative to previous years. According to the mortality analysis by mixed-effects logistic regression, individual risk factors associated with 30-day mortality after a COVID-19 diagnosis were age (OR 1.58 95%CI 1.35 to 1.85 per additional 10 years), male sex (OR 2.37 95%CI 1.70 to 3.32), loss of autonomy (OR 1.12 95%CI 1.05 to 1.20 per unit increase of Iso-SMAF profile), C-level (OR 3.43 95%CI 1.57 to 7.51) or D-level (OR 3.61 95%CI 1.47 to 8.89) medical intervention compared to A-level, as well as being diagnosed with a neurocognitive disorder (OR 1.54 95%CI 1.04 to 2.29) or congestive heart failure (OR 2.36 95%CI 1.45 to 3.85). Treatment with thromboprophylaxis (OR 0.42 95%CI 0.29 to 0.63) and diagnosis after April 20, 2020 (OR 0.46 95%CI 0.33 to 0.65) were associated with 30-day survival. As for institutional risk factors, severe shortage of auxiliary nurses (OR 1.91 95%CI 1.14 to 3.21) and facility size (OR 1.77 95%CI 1.17 to 2.68 per 100 beds) increased the odds of dying within 30 days. Conclusion: This study identified several modifiable risk factors at the institutional level associated with COVID-19 infections and deaths, including testing strategies, adherence to ministry directives for infection prevention, auxiliary nurse shortages, and number of beds per facility. Future policies and regulations targeting long-term care facilities will need to tackle these critical issues, for this pandemic and beyond.

Coronavirus disease 2019 (COVID-19), an infectious respiratory disease propagated by a new virus known as Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), has resulted in global healthcare crises. Emerging evidence from patients with COVID-19 suggests that endothelial cell damage plays a central role in COVID-19 pathogenesis and could be a major contributor to the severity and mortality of COVID-19. Like other infectious diseases, the pathogenesis of COVID-19 is closely associated with metabolic processes. Lactate, a potential biomarker in COVID-19, has recently been shown to mediate endothelial barrier dysfunction. In this review, we provide an overview of cardiovascular injuries and metabolic alterations caused by SARS-CoV-2 infection. We also propose that lactate plays a potential role in COVID-19-driven endothelial cell injury.

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<p dir="ltr">Infectious diseases are caused by a multitude of organisms, ranging from viruses to bacteria, from parasites to fungi, and can be passed directly or indirectly from one person to another. Further, they continue to be a leading cause of death, especially in low-resource countries, thereby emphasizing the need for continued investigation. Understanding transmission of such diseases is vital as management or prevention of outbreaks through detection, reporting, isolation, and case management are ever-evolving. One way by which scientists can study infectious diseases is through a combination of epidemiological, genomic, and evolutionary biology approaches. This doctoral research occurred precisely at this interface, spanning across the fields of genomics, molecular biology, and epidemiology, as applied to the study of infectious disease dynamics of two separate pathogen systems (protozoan and virus).</p><p dir="ltr">The first half of this research (Chapters 1 + 2) involved the implementation of SARS-CoV-2 genomic sequencing and surveillance at Purdue University. Through this investigation in a university setting (Chapter 1), this work identified relevant variants of concern in hundreds of newly sequenced viral genomes and compared variant temporal trends with other similar university settings using publicly available data. Further phylodynamic analysis of Gamma (P.1) genomes from campus revealed multiple introductions into the Purdue community, predominantly from states within the United States. A second study (Chapter 2) assessed the transmission of variants over the course of an entire academic year from 2021-2022 in Purdue’s highly vaccinated community. This research described the rapid transition from Delta to Omicron variants and investigated variant introduction events into the campus. This comprehensive analysis showed that robust surveillance programs coupled with viral genomic sequencing and phylogenetic analysis can provide critical insights into SARS-CoV-2 spread and can help inform mitigation strategies for future pandemics.</p><p dir="ltr">The latter half of this body of research (Chapters 3 + 4) focused on malaria, which is a disease caused by <i>Plasmodium </i>species<i> </i>parasites and transmitted to humans through the bites of infected mosquitoes. The first investigation explored diagnostic accuracy metrics across a malaria transmission gradient in Zambia through a comparison of the diagnostic performance of Rapid Diagnostic Tests (RDT) and Light Microscopy (LM) with photo-induced electron transfer polymerase chain reaction (PET-PCR) as the gold standard using 2018 Malaria Indicator Survey (MIS) data. Results suggested that RDTs and LM both performed well across a range of transmission intensities, but low parasitaemia infections can affect accuracy. This suggests that more sensitive tools should be utilized to identify the last cases as Zambia moves towards malaria elimination. In addition to diagnostic metrics, preventing disease is also crucial for infectious diseases, and vaccines present one mechanism by which this can be done. Research to develop a malaria vaccine with sustained high efficacy has spanned decade. However, the process has proven to be challenging, with several vaccine candidates having advanced to early-stage trials, but only a few demonstrating sustained efficacy in clinical testing. The goal of the last investigation (Chapter 4) was to shed light on the diversity of <i>Plasmodium falciparum </i>antigens which could be considered when developing future malaria vaccines. Results of evolutionary and genomic analyses of Whole-Genome-Sequences from Zambia and other countries in Africa suggest that conserved merozoite antigens and/or transmission-blocking antigens should be prioritized when developing future malaria vaccines.</p>

40% of severe acute respiratory syndrome coronavirus two (SARS-CoV-2) severe cases develop acute kidney injury (AKI). Current treatment for renal complications limits financial and material resources available. To explore alternative treatments and accelerate research in case of future coronavirus outbreaks, a mouse model of coronavirus disease 2019-associated AKI (C19-AKI) would represent a critical biomedical research tool. The surrogate model of C19-AKI (SMC) developed consisted of angiotensin-converting enzyme two (ACE2) knockout (KO) mice receiving 400 ng/kg/min of angiotensin (Ang) II by osmotic minipump for eight days with a single injection of lipopolysaccharide (LPS; 10 mg/kg) on the seventh day of Ang II and euthanasia 24 hours after LPS. Similarly, to C19-AKI, the SMC exhibited albuminuria, elevated blood urea nitrogen, electrolyte imbalance, neutrophil infiltration, and upregulation of the G-coupled protein receptor (GPR)84 and pro-inflammatory and injury markers. GPR84 was found in bronchoalveolar lavage fluid neutrophils of coronavirus disease 2019 (COVID-19) patients, suggesting a potential implication of GPR84 in the disease. We hypothesised that GPR84 deletion or antagonism with GLPG-1205 could attenuate SMC’s indices of renal injury and inflammation. GLPG-1205 and GPR84 KO had no effects in the SMC model, as suggested by unchanged albuminuria, electrolytes, and markers expression. Interestingly, neutrophil infiltration was attenuated by GLPG-1205 only. The SMC is an interesting tool for therapeutic development for infections associated with renal injury, such as SARS-CoV-2. GPR84 role in the SMC needs to be further assessed.