SARS-Cov 2 infection and anti-tuberculosis immunity: temporal association or real protective role?

Introduction: According to the literature consulted to date, there is epidemiological heterogeneity of covid 19 between countries depending on their vaccination policy, in particular BCG vaccination. These findings have led to several hypotheses, including the protective role of immunity induced by the BCG tuberculosis vaccine against Covid-19 infection. The immunity induced by the BCG vaccine significantly increases the secretion of pro-inflammatory cytokines, in particular IL-1B, which has been shown to play an essential role in antiviral immunity. This cross-immunity, although not specific, if highlighted, is a real providence that must be taken advantage of in the face of this pandemic. The main objective of this study is to rule out or confirm that anti-tuberculosis immunity protects against SARS-COV 2 in our context. Materiel and methods: Two groups will be compared: cases infected with the virus and controls who have never been infected with the virus. Both case and control groups will undergo a tuberculin skin test: the intra dermal tuberculin reaction (IDR). Results: We found that our control group had a high IDR immunity value, with an IDR tuberculin positive percentage of 67.2%. This suggests that immunity to IDR is a protective factor against coronavirus disease. Conclusion: The hypothesis of nonspecific anti-tuberculosis protection deserves further verification studies; it would have large positive repercussions for developing countries.

Vaccine-induced immune responses against SARS-CoV-2 infections

Vaccination against coronavirus disease 2019 (COVID-19) is one of the most effective tools to curb the pandemic. Multiple vaccine candidates based on different platforms are available for emergency use presently. However, in common all the vaccines target spike protein, which is a dominant immunogen of severe acute respiratory syndrome corona virus 2 (SARS-CoV-2). Adequate immunogenicity and efficacy are demonstrated by many of the vaccines in clinical phase III trials. The emergence of the new variant of concern is believed to be associated with less susceptibility to the post-infection or post-vaccination mounted immunity. It is a global concern currently threatening the progression of the vaccination drive. Nevertheless, the results of the presently available phase III clinical trials promote COVID-19 vaccination to prevent disease severity and COVID-19 related deaths. Cross-immunity towards the new variants of concern especially against the South African variant is yet to be explored and managed adequately.

SARS-Cov 2 infection and anti-tuberculosis immunity: temporal association or real protective role?

Introduction: According to the literature consulted to date, there is epidemiological heterogeneity of covid 19 between countries depending on their vaccination policy, in particular BCG vaccination. These findings have led to several hypotheses, including the protective role of immunity induced by the BCG tuberculosis vaccine against Covid-19 infection. The immunity induced by the BCG vaccine significantly increases the secretion of pro-inflammatory cytokines, in particular IL-1B, which has been shown to play an essential role in antiviral immunity. This cross-immunity, although not specific, if highlighted, is a real providence that must be taken advantage of in the face of this pandemic. The main objective of this study is to rule out or confirm that anti-tuberculosis immunity protects against SARS-COV 2 in our context. Materiel and methods: Two groups will be compared: cases infected with the virus and controls who have never been infected with the virus. Both case and control groups will undergo a tuberculin skin test: the intra dermal tuberculin reaction (IDR). Results: We found that our control group had a high IDR immunity value, with an IDR tuberculin positive percentage of 67.2%. This suggests that immunity to IDR is a protective factor against coronavirus disease. Conclusion: The hypothesis of nonspecific anti-tuberculosis protection deserves further verification studies; it would have large positive repercussions for developing countries.

COVID-19: Cross Reactive Immunity, Herd Immunity, and Convalescent Serum Therapy

Objective: To present various types of vaccines and viral infections which can induce cross-reactive immunity against COVID-19. In addition, this article discusses the role of herd immunity and convalescent serum therapy in preventing and controlling SARS CoV-2. The study also determined the claims and counterclaims about their protective and therapeutic effects. Method: Non-systematic review was done using different articles done on cross-reactive immunity against COVID-19 through vaccinations, previous infections, herd immunity and the therapeutic effects of convalescence serum. The search was done on the PubMed, Google Scholar, and Science Direct, WHO, Euro-surveillance, CDC databases. Results: Many observational correlational studies reported that BCG decreases the incidence and mortality from COVID-19. Furthermore, homology between the COVID-19 virus and the measles, mumps, and rubella (MMR) viruses was discovered. Few studies suggested the presence of cross-immunity between MMR vaccine and SARS-CoV-2. Similarly, few studies suggested protective effects of Oral Polio Vaccine (OPV) against SARS-CoV-2; since both viruses are positive-single-strand RNA (+ssRNA). Diphtheria, pertussis, and tetanus (DPT) vaccines, particularly those that include inactivated whole pertussis vaccine, might induce B and T cell cross-reactive immunity against SARS-CoV-2. Other vaccines against Streptococcus pneumonia, Haemophilus influenza, and Meningococcal meningitis vaccines are suggested also to induce some immunity against Covid-19. It is hypothesized that infections with other Coronaviruses may cause protection against SARS-CoV-2. However, the studies done on these suggestions were mostly observational that can carry a high chance of inherent biases. There are also claims and counterclaims about the effect of herd immunity and convalescence serum on the prevention and control of Covid-19. So, appropriately designed RCTs are needed to prove or disprove their protective and therapeutic effects. Conclusions: There are claims and counterclaims about the protective effects of different vaccines, previous infections, and herd immunity and regarding the therapeutic effects of convalescence serum. Comparing with other vaccines, BCG was suggested to have the highest cross-reactive epitopes against SARS-Cov-2 virus. MMR, OPV, DPT, Influenza, Pneumococcal and meningococcal vaccines are suggested to protect against Covid-19. Previous infection with other Corona viruses, herd immunity and convalescence serum may play roles in the prevention and control of Covid-19. Many large clinical trials are undergoing nowadays and their results are needed to prove or disprove the cross-immunity related to SARS-CoV-2 and the effect of convalescence serum.

Reconstructing contact network structure and cross-immunity patterns from multiple infection histories

Interactions within a population shape the spread of infectious diseases but contact patterns between individuals are difficult to access. We hypothesised that key properties of these patterns can be inferred from multiple infection data in longitudinal follow-ups. We developed a simulator for epidemics with multiple infections on networks and analysed the resulting individual infection time series by introducing similarity metrics between hosts based on their multiple infection histories. We find that, depending on infection multiplicity and network sampling, multiple infection summary statistics can recover network properties such as degree distribution. Furthermore, we show that by mining simulation outputs for multiple infection patterns, one can detect immunological interference between pathogens (i.e. the fact that past infections in a host condition future probability of infection). The combination of individual-based simulations and analysis of multiple infection histories opens promising perspectives to infer and validate transmission networks and immunological interference for infectious diseases from longitudinal cohort data.

Effect of human behavior on the evolution of viral strains during an epidemic

It is well known in the literature that human behavior can change as a reaction to disease observed in others, and that such behavioral changes can be an important factor in the spread of an epidemic. It has been noted that human behavioral traits in disease avoidance are under selection in the presence of infectious diseases. Here we explore a complimentary trend: the pathogen itself might experience a force of selection to become less “visible”, or less “symptomatic”, in the presence of such human behavioral trends. Using a stochastic SIR agent-based model, we investigated the co-evolution of two viral strains with cross-immunity, where the resident strain is symptomatic while the mutant strain is asymptomatic. We assumed that individuals exercised self-regulated social distancing (SD) behavior if one of their neighbors was infected with a symptomatic strain. We observed that the proportion of asymptomatic carriers increased over time with a stronger effect corresponding to higher levels of self-regulated SD. Adding mandated SD made the effect more significant, while the existence of a time-delay between the onset of infection and the change of behavior reduced the advantage of the asymptomatic strain. These results were consistent under random geometric networks, scale-free networks, and a synthetic network that represented the social behavior of the residents of New Orleans.

Hyperendemicity associated with increased dengue burden

Over 105 million dengue infections are estimated to occur annually. Understanding the disease dynamics of dengue is often difficult due to multiple strains circulating within a population. Interactions between dengue serotype dynamics may result in complex cross-immunity dynamics at the population level and create difficulties in terms of formulating intervention strategies for the disease. In this study, a nationally representative 16-year time series with over 43 000 serotyped dengue infections was used to infer the long-run effects of between and within strain interactions and their impacts on past outbreaks. We used a novel identification strategy incorporating sign-identified Bayesian vector autoregressions, using structural impulse responses, historical decompositions and counterfactual analysis to conduct inference on dengue dynamics post-estimation. We found that on the population level: (i) across-serotype interactions on the population level were highly persistent, with a one time increase in any other serotype associated with long run decreases in the serotype of interest (range: 0.5–2.5 years) and (ii) over 38.7% of dengue cases of any serotype were associated with across-serotype interactions. The findings in this paper will substantially impact public health policy interventions with respect to dengue.

Cross-reactive CD4+ T cells enhance SARS-CoV-2 immune responses upon infection and vaccination

The functional relevance of pre-existing cross-immunity to SARS-CoV-2 is a subject of intense debate. Here, we show that human endemic coronavirus (HCoV)-reactive and SARS-CoV-2-cross-reactive CD4+ T cells are ubiquitous but decrease with age. We identified a universal immunodominant coronavirus-specific spike peptide (S816-830) and demonstrate that pre-existing spike- and S816-830-reactive T cells were recruited into immune responses to SARS-CoV-2 infection and their frequency correlated with anti-SARS-CoV-2-S1-IgG antibodies. Spike-cross-reactive T cells were also activated after primary BNT162b2 COVID-19 mRNA vaccination displaying kinetics similar to secondary immune responses. Our results highlight the functional contribution of pre-existing spike-cross-reactive T cells in SARS-CoV-2 infection and vaccination. Cross-reactive immunity may account for the unexpectedly rapid induction of immunity following primary SARS-CoV-2 immunization and the high rate of asymptomatic/mild COVID-19 disease courses.

Agent-based Investigation of the Impact of Low Rates of Influenza on Next Season Influenza Infections

IntroductionInterventions to curb the spread of SARS-CoV-2 during the 2020-21 influenza season essentially eliminated influenza during that season. Given waning antibody titers over time, future residual population immunity against influenza will be reduced. The implication for the subsequent 2021-22 influenza season is unknown.MethodsWe used an agent-based model of influenza implemented in the FRED (Framework for Reconstructing Epidemiological Dynamics) simulation platform to estimate cases and hospitalization over two succeeding influenza seasons. The model uses a synthetic population to represent an actual population, and individual interactions in workplaces, school, households and neighborhoods. The impact of reduced residual immunity was estimated as a consequence of increased protective measures (e.g., social distancing and school closure) in the first season. The impact was contrasted by the level of similarity (cross-immunity) between influenza strains over the seasons.ResultsWhen the second season strains were dissimilar to the first season (have a low level of cross immunity), a low first season has limited impact on second season cases. When a high level of cross-immunity exists between strains in the 2 seasons, the first season has a much greater impact on the second season. In both cases this is modified by the transmissibility of strains in the 2 seasons. In the context of the 2021-22 season, the worst case scenario is a highly transmissible strain causing increased cases and hospitalizations over average influenza seasons, with a possible significant increase in cases in some scenarios. The most likely overall scenario for 2021-22 is a more modest increase in flu cases over an average season.DiscussionGiven the light 2020-21 season, we found that a large, compensatory second season might occur in 2021-22, depending on cross-immunity from past infection and transmissibility of strains. Furthermore, we found that enhanced vaccine coverage could reduce this high, compensatory season. Young children may be especially at risk in 2021-22 since very young children were unlikely to have had any exposure to infection and most immunity in that age group would be from vaccination, which wanes quickly.

Cross immunity protection and antibody dependent enhancement: A distributed delay dynamic model

Dengue fever is endemic in tropical and sub-tropical countries, and some of the important features of Dengue fever spread continues to pose challenges for mathematical modelling. Here, we propose a system of integro-differential equations (IDE) to study the disease transmission dynamics that involves multiserotypes and cross immunity. Our main objective is to incorporate and analyze the effect of a general time delay term describing acquired cross immunity protection and the effect of antibody dependent enhancement (ADE), both characteristics of Dengue fever. We perform qualitative analysis of the model and obtain results to show the stability of the epidemiologically important steady solutions that is completely determined by the basic reproduction number and the invasion reproduction number. We establish the global dynamics, by constructing suitable Lyapunov functions. We also conduct some numerical experiments to illustrate bifurcation structures, indicating the occurrence of periodic oscillations for specific range of values of a key parameter representing the ADE.