Kinetics of antibody responses dictate COVID-19 outcome

Mucosal immunization with lactiplantibacillus plantarum-displaying recombinant SARS-CoV-2 epitopes on the surface induces humoral and mucosal immune responses in mice

BACKGROUND

The use of probiotic lactic acid bacteria as a mucosal vaccine vector is considered a promising alternative compared to the use of other microorganisms because of its "Generally Regarded as Safe" status, its potential adjuvant properties, and its tolerogenicity to the host. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease (COVID-19), is highly transmissible and pathogenic. This study aimed to determine the potential of Lactiplantibacillus plantarum expressing SARS-CoV-2 epitopes as a mucosal vaccine against SARS-CoV-2.

RESULTS

In this study, the possible antigenic determinants of the spike (S1-1, S1-2, S1-3, and S1-4), membrane (ME1 and ME2), and envelope (E) proteins of SARS-CoV-2 were predicted, and recombinant L. plantarum strains surface-displaying these epitopes were constructed. Subsequently, the immune responses induced by these recombinant strains were compared in vitro and in vivo. Most surface-displayed epitopes induced pro-inflammatory cytokines [tumor necrosis factor alpha (TNF-α and interleukin (IL)-6] and anti-inflammatory cytokines (IL-10) in lipopolysaccharide-induced RAW 264.7, with the highest anti-inflammatory to pro-inflammatory cytokine ratio in the S1-1 and S1-2 groups, followed by that in the S1-3 group. When orally administered of recombinant L. plantarum expressing SARS-CoV-2 epitopes in mice, all epitopes most increased the expression of IL-4, along with induced levels of TNF-α, interferon-gamma, and IL-10, specifically in spike protein groups. Thus, the surface expression of epitopes from the spike S1 protein in L. plantarum showed potential immunoregulatory effects, suggesting its ability to potentially circumvent hyperinflammatory states relevant to monocyte/macrophage cell activation. At 35 days post immunization (dpi), serum IgG levels showed a marked increase in the S1-1, S1-2, and S1-3 groups. Fecal IgA levels increased significantly from 21 dpi in all the antigen groups, but the boosting effect after 35 dpi was explicitly observed in the S1-1, S1-2, and S1-3 groups. Thus, the oral administration of SARS-CoV-2 antigens into mice induced significant humoral and mucosal immune responses.

CONCLUSION

This study suggests that L. plantarum is a potential vector that can effectively deliver SARS-CoV-2 epitopes to intestinal mucosal sites and could serve as a novel approach for SARS-CoV-2 mucosal vaccine development.

Epitope Coverage of Anti-SARS-CoV-2 Nucleocapsid IgA and IgG Antibodies Correlates with Protection against Re-Infection by New Variants in Subsequent Waves of the COVID-19 Pandemic

The COVID-19 pandemic continues to affect individuals across the globe, with some individuals experiencing more severe disease than others. The relatively high frequency of re-infections and breakthrough infections observed with SARS-CoV-2 highlights the importance of extending our understanding of immunity to COVID-19. Here, we aim to shed light on the importance of antibody titres and epitope utilization in protection from re-infection. Health care workers are highly exposed to SARS-CoV-2 and are therefore also more likely to become re-infected. We utilized quantitative, multi-antigen, multi-epitope SARS-CoV-2 protein microarrays to measure IgG and IgA titres against various domains of the nucleocapsid and spike proteins. Potential re-infections in a large, diverse health care worker cohort (N = 300) during the second wave of the pandemic were identified by assessing the IgG anti-N titres before and after the second wave. We assessed epitope coverage and antibody titres between the 'single infection' and 're-infection' groups. Clear differences were observed in the breadth of the anti-N response before the second wave, with the epitope coverage for both IgG (p = 0.019) and IgA (p = 0.015) being significantly increased in those who did not become re-infected compared to those who did. Additionally, the IgG anti-N (p = 0.004) and anti-S titres (p = 0.018) were significantly higher in those not re-infected. These results highlight the importance of the breadth of elicited antibody epitope coverage following natural infection in protection from re-infection and disease in the COVID-19 pandemic.

A Review on Immunological Responses to SARS-CoV-2 and Various COVID-19 Vaccine Regimens

The transmission of SARS-CoV-2 has caused serious health crises globally. So far, 7 vaccines that are already being assessed in Phase IV clinical trials are, Comirnaty/ Pfizer; Spikevax/Moderna (m RNA vaccine); Vaxzevria or Covishield; Ad26.COV2.S; Ad5-nCoV (adenoviral vector-based vaccine); CoronaVac and BBIBP-CorV (inactivated virus vaccine). Besides, there are about 280 vaccines that are undergoing preclinical and clinical trials including Sputnik-V, Covaxin or BBV152, and NVX-CoV2373. These vaccines are being studied for their immunological responses and efficiency against COVID-19, and have been reported to demonstrate effective T and B cell responses. However, the long-lasting immunity of these vaccine regimens still needs to be investigated. An in-depth understanding of the vaccine efficacy and immune control mechanism is imperative for the rational purposing and implementation of the vaccines. Hence, in this review, we have comprehensively discussed the immune response induced in COVID-19 patients, as well as in the convalescent individuals to avoid reinfection. Moreover, we have also summarized the immunological responses and prophylactic efficacy of various COVID-19 vaccine regimens. In this context, this review can give insights into the development of effective vaccines against SARS-CoV-2 and its variants in the future.

Machine learning to support visual auditing of home-based lateral flow immunoassay self-test results for SARS-CoV-2 antibodies

Background

Lateral flow immunoassays (LFIAs) are being used worldwide for COVID-19 mass testing and antibody prevalence studies. Relatively simple to use and low cost, these tests can be self-administered at home, but rely on subjective interpretation of a test line by eye, risking false positives and false negatives. Here, we report on the development of ALFA (Automated Lateral Flow Analysis) to improve reported sensitivity and specificity.

Methods

Our computational pipeline uses machine learning, computer vision techniques and signal processing algorithms to analyse images of the Fortress LFIA SARS-CoV-2 antibody self-test, and subsequently classify results as invalid, IgG negative and IgG positive. A large image library of 595,339 participant-submitted test photographs was created as part of the REACT-2 community SARS-CoV-2 antibody prevalence study in England, UK. Alongside ALFA, we developed an analysis toolkit which could also detect device blood leakage issues.

Results

Automated analysis showed substantial agreement with human experts (Cohen's kappa 0.90-0.97) and performed consistently better than study participants, particularly for weak positive IgG results. Specificity (98.7-99.4%) and sensitivity (90.1-97.1%) were high compared with visual interpretation by human experts (ranges due to the varying prevalence of weak positive IgG tests in datasets).

Conclusions

Given the potential for LFIAs to be used at scale in the COVID-19 response (for both antibody and antigen testing), even a small improvement in the accuracy of the algorithms could impact the lives of millions of people by reducing the risk of false-positive and false-negative result read-outs by members of the public. Our findings support the use of machine learning-enabled automated reading of at-home antibody lateral flow tests as a tool for improved accuracy for population-level community surveillance.

Epidemiological study in a small rural area of Veneto (Italian region) during Sars-Cov-2 Pandemia

The emergence of severe acute respiratory syndrome type 2 coronavirus (SARS-CoV-2) and its complications have demonstrated the devastating impact of a new infectious pathogen. The organisational change promulgated by the isolation of affected communities is of extreme importance to achieve effective containment of the contagion and good patient care. The epidemiological study of the population of a small rural community in the North East of Italy revealed how much the virus had circulated during Spring, 2020, and how contagion has evolved after a prolonged lockdown. In the 1st phase, NAAT (Nucleic Acid Amplification Testing) was performed in cases with more or less severe symptoms and a study was performed to trace the infection of family members. Only 0.2% of the population tested positive on NAAT, via nasopharyngeal swab during this 1st phase. In the 2nd phase a random sample of the general population were tested for circulating anti-Sars-Cov-2 immunoglobulins. This showed that approximately 97.9% of the population were negative, while 2.1% (with positive IgG at a distance) of the population had contracted the virus in a mildly symptomatic or asymptomatic form. The main symptom in subjects who developed immunity was fever. Antibodies were found in subjects with forced coexistence with quarantined or infected subjects. The mutual spatial distance by categories has shown higher relative prevalence of IgG positive and IgM negative cases in close proximity but also far from the infected, with respect to an intermediate distance. This suggests that subjects living in thinly populated areas could come in contact with the virus more likely due to intentional/relational proximity, while those living nearby could also be infected through random proximity.

Seroprevalence of Antibodies to SARS-CoV-2 in Guangdong Province, China between March to June 2020

Guangdong province, located in South China, is an important economic hub with a large domestic migrant population and was among the earliest areas to report COVID-19 cases outside of Wuhan. We conducted a cross-sectional, age-stratified serosurvey to determine the seroprevalence of antibodies against SARS-CoV-2 after the emergence of COVID-19 in Guangdong. We tested 14,629 residual serum samples that were submitted for clinical testing from 21 prefectures between March and June 2020 for SARS-CoV-2 antibodies using a magnetic particle based chemiluminescent enzyme immunoassay and validated the results using a pseudovirus neutralization assay. We found 21 samples positive for SARS-CoV-2 IgG, resulting in an estimated age- and sex-weighted seroprevalence of 0.15% (95% CI: 0.06–0.24%). The overall age-specific seroprevalence was 0.07% (95% CI: 0.01–0.24%) in persons up to 9 years old, 0.22% (95% CI: 0.03–0.79%) in persons aged 10–19, 0.16% (95% CI: 0.07–0.33%) in persons aged 20–39, 0.13% (95% CI: 0.03–0.33%) in persons aged 40–59 and 0.18% (95% CI: 0.07–0.40%) in persons ≥60 years old. Fourteen (67%) samples had pseudovirus neutralization titers to S-protein, suggesting most of the IgG-positive samples were true-positives. Seroprevalence of antibodies to SARS-CoV-2 was low, indicating that there were no hidden epidemics during this period. Vaccination is urgently needed to increase population immunity to SARS-CoV-2.

Data-driven operation of the resilient electric grid: A case of COVID-19

Electrical energy is a vital part of modern life, and expectations for grid resilience to allow a continuous and reliable energy supply has tremendously increased even during adverse events (e.g. Ukraine cyberattack, Hurricane Maria). The global pandemic COVID-19 has raised the electric energy reliability risk due to potential workforce disruptions, supply chain interruptions, and increased possible cybersecurity threats. Additionally, the pandemic introduces a significant degree of uncertainty to the grid operation in the presence of other challenges including aging power grids, high proliferation of distributed generation, market mechanism, and active distribution network. This situation increases the need for measures for the resiliency of power grids to mitigate the impact of the pandemic as well as simultaneous extreme events including cyberattacks and adverse weather events. Solutions to manage such an adverse scenario will be multi-fold: (a) emergency planning and organisational support, (b) following safety protocol, (c) utilising enhanced automation and sensing for situational awareness, and (d) integration of advanced technologies and data points for ML-driven enhanced decision support. Enhanced digitalisation and automation resulted in better network visibility at various levels, including generation, transmission, and distribution. These data or information can be employed to take advantage of advanced machine learning techniques for automation and increased power grid resilience. In this paper, the resilience of power grids in the face of pandemics is explored and various machine learning tools that can be helpful to augment human operators are discused by: (a) reviewing the impact of COVID-19 on power grid operations and actions taken by operators/organisations to minimise the impact of COVID-19, and (b) presenting recently developed tools and concepts of machine learning and artificial intelligence that can be applied to increase the resiliency of power systems in normal and extreme scenarios such as the COVID-19 pandemic.

Research on bilingualism as discovery science

An important aim of research on bilingualism is to understand how the brain adapts to the demands of using more than one language.In this paper, we argue that pursuing such an aim entails valuing our research as a discovery process that acts on variety.Prescriptions about sample size and methodology, rightly aimed at establishing a sound basis for generalization, should be understood as being in the service of science as a discovery process. We propose and illustrate by drawing from previous and contemporary examples within brain and cognitive sciences, that this necessitates exploring the neural bases of bilingual phenotypes:the adaptive variety induced through the interplay of biology and culture. We identify the conceptual and methodological prerequisites for such exploration and briefly allude to the publication practices that afford it as a community practice and to the risk of allowing methodological prescriptions, rather than discovery, to dominate the research endeavor.

Serological assessment of SARS-CoV-2 infection during the first wave of the pandemic in Louisville Kentucky

Serological assays intended for diagnosis, sero-epidemiologic assessment, and measurement of protective antibody titers upon infection or vaccination are essential for managing the SARS-CoV-2 pandemic. Serological assays measuring the antibody responses against SARS-CoV-2 antigens are readily available. However, some lack appropriate characteristics to accurately measure SARS-CoV-2 antibodies titers and neutralization. We developed an Enzyme-linked Immunosorbent Assay (ELISA) methods for measuring IgG, IgA, and IgM responses to SARS-CoV-2, Spike (S), receptor binding domain (RBD), and nucleocapsid (N) proteins. Performance characteristics of sensitivity and specificity have been defined. ELISA results show positive correlation with microneutralization and Plaque Reduction Neutralization assays with infectious SARS-CoV-2. Our ELISA was used to screen healthcare workers in Louisville, KY during the first wave of the local pandemic in the months of May and July 2020. We found a seropositive rate of approximately 1.4% and 2.3%, respectively. Our analyses demonstrate a broad immune response among individuals and suggest some non-RBD specific S IgG and IgA antibodies neutralize SARS-CoV-2.

Susceptibility to Severe Acute Respiratory Syndrome Coronavirus 2 Infection Among Children and Adults: A Seroprevalence Study of Family Households in the Barcelona Metropolitan Region, Spain

Background

Susceptibility of children and adults to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and persistence of antibody response to the virus after infection resolution remain poorly understood, despite their significant public health implications.

Methods

A prospective cross-sectional seroprevalence study with volunteer families that included at least 1 first-reported adult case positive by SARS-CoV-2 by polymerase chain reaction (PCR) and at least 1 child aged <15 years living in the same household under strict home confinement was conducted in the metropolitan Barcelona Health Region, Spain, during the pandemic period 28 April 2020–3 June 2020. All household members were tested at home using a rapid SARS-CoV-2 antibody assay with finger prick–obtained capillary blood.

Results

A total of 381 family households including 381 first-reported PCR-positive adult cases and 1084 contacts (672 children, 412 adults) were enrolled. SARS-CoV-2 seroprevalence rates were 17.6% (118 of 672) in children and 18.7% (77 of 335) in adult contacts (P = .64). Among first-reported cases, seropositivity rates varied from 84.0% in adults previously hospitalized and tested within 6 weeks since the first positive PCR result to 31.5% in those not hospitalized and tested after that lag time (P < .001). Nearly all (99.9%) positive children were asymptomatic or had mild symptoms.

Conclusions

Children appear to have similar probability as adults to become infected by SARS-CoV-2 in quarantined family households but remain largely asymptomatic. Adult antibody protection against SARS-CoV-2 seems to be weak beyond 6 weeks post-infection confirmation, especially in cases that have experienced mild disease.

Human mobility and poverty as key drivers of COVID-19 transmission and control

BACKGROUND

Applying heavy nationwide restrictions is a powerful method to curtail COVID-19 transmission but poses a significant humanitarian and economic crisis. Thus, it is essential to improve our understanding of COVID-19 transmission, and develop more focused and effective strategies. As human mobility drives transmission, data from cellphone devices can be utilized to achieve these goals.

METHODS

We analyzed aggregated and anonymized mobility data from the cell phone devices of> 3 million users between February 1, 2020, to May 16, 2020 - in which several movement restrictions were applied and lifted in Israel. We integrated these mobility patterns into age-, risk- and region-structured transmission model. Calibrated to coronavirus incidence in 250 regions covering Israel, we evaluated the efficacy and effectiveness in decreasing morbidity and mortality of applying localized and temporal lockdowns (stay-at-home order).

RESULTS

Poorer regions exhibited lower and slower compliance with the restrictions. Our transmission model further indicated that individuals from impoverished areas were associated with high transmission rates. Considering a horizon of 1-3 years, we found that to reduce COVID-19 mortality, school closure has an adverse effect, while interventions focusing on the elderly are the most efficient. We also found that applying localized and temporal lockdowns during regional outbreaks reduces the overall mortality and morbidity compared to nationwide lockdowns. These trends were consistent across vast ranges of epidemiological parameters, and potential seasonal forcing.

CONCLUSIONS

More resources should be devoted to helping impoverished regions. Utilizing cellphone data despite being anonymized and aggregated can help policymakers worldwide identify hotspots and apply designated strategies against future COVID-19 outbreaks.

Serological Evaluation of Human Antibodies of the Immunoglobulin Class A and G Against SARS-CoV-2 in Serum Collected in Newfoundland and Labrador

The ability to detect antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently under investigation with various performance characteristics and indications for use. In this article, we analyzed the ability of the Abbott SARS-CoV-2 immunoglobulin class G (IgG), EuroImmun SARS-CoV-2 enzyme-linked immunosorbent assay (ELISA) IgG, and EuroImmun SARS-CoV-2 ELISA immunoglobulin class A (IgA) kits to detect evidence of previous infection with SARS-CoV-2. We tested 49 known coronavirus disease-19 (COVID-19) patients and 111 prepandemic stored serology specimens. This resulted in a sensitivity of 95.9%, 100.0%, and 91.3% and a specificity of 98.2%, 98.2%, and 90.8% respectively, using manufacturer recommended cutoffs after inconclusive results (one for EuroImmun IgG and five for EuroImmun IgA) being excluded in the final statistical analyses. Cross-reactivity of hepatitis C virus seropositive specimens was observed resulting in false positives (p < 0.05). If a two-tiered algorithmic approach was applied, that is, testing with Abbott SARS-CoV-2 assay followed by EuroImmun SARS-CoV-2 IgG, 100% specificity and sensitivity could be obtained after six inconclusive results were excluded from data set before statistical analyses. Performance characteristics presented demonstrate the superior performance of IgG class antibodies for investigating previous infections. In addition, utilizing a second antibody test for supplementary testing may significantly enhance performance, particularly in lower prevalence settings.

Dromedary camels as a natural source of neutralizing nanobodies against SARS-CoV-2

The development of prophylactic and therapeutic agents for coronavirus disease 2019 (COVID-19) is a current global health priority. Here, we investigated the presence of cross-neutralizing antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in dromedary camels that were Middle East respiratory syndrome coronavirus (MERS-CoV) seropositive but MERS-CoV free. The tested 229 dromedaries had anti–MERS-CoV camel antibodies with variable cross-reactivity patterns against SARS-CoV-2 proteins, including the S trimer and M, N, and E proteins. Using SARS-CoV-2 competitive immunofluorescence immunoassays and pseudovirus neutralization assays, we found medium-to-high titers of cross-neutralizing antibodies against SARS-CoV-2 in these animals. Through linear B cell epitope mapping using phage immunoprecipitation sequencing and a SARS-CoV-2 peptide/proteome microarray, we identified a large repertoire of Betacoronavirus cross-reactive antibody specificities in these dromedaries and demonstrated that the SARS-CoV-2–specific VHH antibody repertoire is qualitatively diverse. This analysis revealed not only several SARS-CoV-2 epitopes that are highly immunogenic in humans, including a neutralizing epitope, but also epitopes exclusively targeted by camel antibodies. The identified SARS-CoV-2 cross-neutralizing camel antibodies are not proposed as a potential treatment for COVID-19. Rather, their presence in nonimmunized camels supports the development of SARS-CoV-2 hyperimmune camels, which could be a prominent source of therapeutic agents for the prevention and treatment of COVID-19.

SARS-CoV-2: phylogenetic origins, pathogenesis, modes of transmission, and the potential role of nanotechnology

The COVID-19 pandemic has elicited a rapid response from the scientific community with significant advances in understanding the causative pathogen (SARS-CoV-2). Mechanisms of viral transmission and pathogenesis, as well as structural and genomic details, have been reported, which are essential in guiding containment, treatment, and vaccine development efforts. Here, we present a concise review of the recent research in these domains and an exhaustive analysis of the genomic origins of SARS-CoV-2. Particular emphasis has been placed on the pathology and disease progression of COVID-19 as documented by recent clinical studies, in addition to the characteristic immune responses involved therein. Furthermore, we explore the potential of nanomaterials and nanotechnology to develop diagnostic tools, drug delivery systems, and personal protective equipment design within the ongoing pandemic context. We present this as a ready resource for researchers to gain succinct, up-to-date insights on SARS-CoV-2.

Corona-Cov-2 (COVID-19) and ginseng: Comparison of possible use in COVID-19 and influenza

In the 1918 influenza pandemic, more than 95% of mortalities were ascribed to bacterial pneumonia. After the primary influenza infection, the innate immune system is attenuated, and the susceptibility to bacteria is increased. Subsequent bacterial pneumonia exacerbates morbidity and increases the mortality rate. Similarly, COVID-19 infection attenuates innate immunity and results in pneumonia. In addition, the current pneumococcal conjugate vaccine may have limited defense against secondary pneumococcal infection after influenza infection. Therefore, until a fully protective vaccine is available, a method of increasing immunity may be helpful. Ginseng has been shown to increase the defense against influenza in clinical trials and animal experiments, as well as the defense against pneumococcal pneumonia in animal experiments. Based on these findings, ginseng is suspected to be helpful for providing immunity against COVID-19.

SARS-CoV-2 antibody prevalence in England following the first peak of the pandemic

England has experienced a large outbreak of SARS-CoV-2, disproportionately affecting people from disadvantaged and ethnic minority communities. It is unclear how much of this excess is due to differences in exposure associated with structural inequalities. Here, we report from the REal-time Assessment of Community Transmission-2 (REACT-2) national study of over 100,000 people. After adjusting for test characteristics and re-weighting to the population, overall antibody prevalence is 6.0% (95% CI: 5.8-6.1). An estimated 3.4 million people had developed antibodies to SARS-CoV-2 by mid-July 2020. Prevalence is two- to three-fold higher among health and care workers compared with non-essential workers, and in people of Black or South Asian than white ethnicity, while age- and sex-specific infection fatality ratios are similar across ethnicities. Our results indicate that higher hospitalisation and mortality from COVID-19 in minority ethnic groups may reflect higher rates of infection rather than differential experience of disease or care.

Prevalence of COVID-19 IgG Antibodies in a Cohort of Municipal First Responders

BACKGROUND

Although first responders (FRs) represent a high-risk group for exposure, little information is available regarding their risk of coronavirus disease 2019 (COVID-19) infection. The purpose of the current study was to determine the serological prevalence of past COVID-19 infection in a cohort of municipal law enforcement (LE) and firefighters (FFs).

METHODS

Descriptive analysis of a de-identified data reporting Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) immunoglobulin G (IgG), or COR2G, serology results for municipal FRs. As part of the serology process, FRs were surveyed for COVID-19-like symptoms since February 2020 and asked to report any prior COVID-19 nasal swab testing. Descriptive statistics and two-sided Chi Square tests with Yates correction were used to compare groups.

RESULTS

Of 318 FRs, 225 (80.2%) underwent serology testing (LE: 163/207 [78.7%]; FF: 92/111 [82.9%]). The prevalence of positive serology for all FRs tested was 3/255 (1.2%). Two LE (1.2%) and one FF (1.1%) had positive serology (P = 1.0). Two hundred and twenty-four FRs responded to a survey regarding prior symptoms and testing. Fifty-eight (25.9%) FRs (44 LE; 14 FFs) reported the presence of COVID-19-like symptoms. Of these, only nine (15.5%) received reverse transcriptase - polymerase chain reaction (RT-PCR) testing; none were positive. Two of the three FRs with positive serology reported no COVID-19-like symptoms and none of these responders had received prior nasal RT-PCR swabs. The overall community positive RT-PCR rate was 0.36%, representing a three-fold higher rate of positive seroprevalence amongst FRs compared with the general population (P = .07).

CONCLUSIONS

Amongst a cohort of municipal FRs with low community COVID-19 prevalence, the seroprevalence of SARS-CoV-19 IgG Ab was three-fold greater than the general community. Two-thirds of positive FRs reported a lack of symptoms. Only 15.5% of FRs with COVID-19-like symptoms received RT-PCR testing. In addition to workplace control measures, increased testing availability to FRs is critical in limiting infection spread and ensuring response capability.

COVID-19 in India: Statewise Analysis and Prediction

BACKGROUND

The highly infectious coronavirus disease (COVID-19) was first detected in Wuhan, China in December 2019 and subsequently spread to 212 countries and territories around the world, infecting millions of people. In India, a large country of about 1.3 billion people, the disease was first detected on January 30, 2020, in a student returning from Wuhan. The total number of confirmed infections in India as of May 3, 2020, is more than 37,000 and is currently growing fast.

OBJECTIVE

Most of the prior research and media coverage focused on the number of infections in the entire country. However, given the size and diversity of India, it is important to look at the spread of the disease in each state separately, wherein the situations are quite different. In this paper, we aim to analyze data on the number of infected people in each Indian state (restricted to only those states with enough data for prediction) and predict the number of infections for that state in the next 30 days. We hope that such statewise predictions would help the state governments better channelize their limited health care resources.

METHODS

Since predictions from any one model can potentially be misleading, we considered three growth models, namely, the logistic, the exponential, and the susceptible-infectious-susceptible models, and finally developed a data-driven ensemble of predictions from the logistic and the exponential models using functions of the model-free maximum daily infection rate (DIR) over the last 2 weeks (a measure of recent trend) as weights. The DIR is used to measure the success of the nationwide lockdown. We jointly interpreted the results from all models along with the recent DIR values for each state and categorized the states as severe, moderate, or controlled.

RESULTS

We found that 7 states, namely, Maharashtra, Delhi, Gujarat, Madhya Pradesh, Andhra Pradesh, Uttar Pradesh, and West Bengal are in the severe category. Among the remaining states, Tamil Nadu, Rajasthan, Punjab, and Bihar are in the moderate category, whereas Kerala, Haryana, Jammu and Kashmir, Karnataka, and Telangana are in the controlled category. We also tabulated actual predicted numbers from various models for each state. All the R2 values corresponding to the logistic and the exponential models are above 0.90, indicating a reasonable goodness of fit. We also provide a web application to see the forecast based on recent data that is updated regularly.

CONCLUSIONS

States with nondecreasing DIR values need to immediately ramp up the preventive measures to combat the COVID-19 pandemic. On the other hand, the states with decreasing DIR can maintain the same status to see the DIR slowly become zero or negative for a consecutive 14 days to be able to declare the end of the pandemic.

Decisions and disease: a mechanism for the evolution of cooperation

In numerous contexts, individuals may decide whether they take actions to mitigate the spread of disease, or not. Mitigating the spread of disease requires an individual to change their routine behaviours to benefit others, resulting in a 'disease dilemma' similar to the seminal prisoner's dilemma. In the classical prisoner's dilemma, evolutionary game dynamics predict that all individuals evolve to 'defect.' We have discovered that when the rate of cooperation within a population is directly linked to the rate of spread of the disease, cooperation evolves under certain conditions. For diseases which do not confer immunity to recovered individuals, if the time scale at which individuals receive accurate information regarding the disease is sufficiently rapid compared to the time scale at which the disease spreads, then cooperation emerges. Moreover, in the limit as mitigation measures become increasingly effective, the disease can be controlled; the number of infections tends to zero. It has been suggested that disease spreading models may also describe social and group dynamics, indicating that this mechanism for the evolution of cooperation may also apply in those contexts.