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In the current SARS-CoV-2 pandemic a key unsolved question is the quality and duration of acquired immunity in recovered individuals. This is crucial to solve, however SARS-CoV-2 has circulated for under five months, precluding a direct study. We therefore monitored 10 subjects over a time span of 35 years (1985-2020), providing a total of 2473 follow up person-months, and determined a) their antibody levels following infection by any of the four seasonal human coronaviruses, and b) the time period after which reinfections by the same virus can occur. An alarmingly short duration of protective immunity to coronaviruses was found by both analyses. We saw frequent reinfections at 12 months post-infection and a substantial reduction in antibody levels as soon as 6 months post-infection.
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ArthurW. D.Edridge1,JoannaKaczorowska1, AlexisC.R.Hoste2,Margreet Bakker1,Michelle Klein1,
Maarten F. Jebbink1, Amy Matser3, Cormac M. Kinsella1, Paloma Rueda2, Maria Prins3,4, Patricia
1. Laboratory of Experimental Virology, Department of Medical Microbiology and Infection
2.INGENASA,InmunoloayGenéticaAplicadaS.A.,Av.delaInstitución Libre de Enseñanza,39, 
4. Amsterdam UMC, University of Amsterdam, Department of Infectious Diseases, Amsterdam
Infection& ImmunityInstitute,AmsterdamUMC,University ofAmsterdam,Meibergdreef15,1105
immunity in recovered individuals. This is crucial to solve, however SARS‐CoV‐2 has circulated for
35years(1985‐2020), providinga total of2473follow upperson‐months,and determineda)their
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probably caused bythefactthatthe virus entered a grossly naive, thus highly susceptible, human
population, combinedwiththecapacity ofthevirusto transmit duringtheasymptomaticphaseof
thatrecovered patientsdevelopprotectiveimmunity.Itisstillunclearwhetherprotectiveimmunity
isindeed inducedafterinfection, andforhowlong.Thedurationofprotectionwillimpactnotonly
of the SARS‐CoV‐1 and MERS‐CoV epidemics. The limited available data on potential protective
coronavirusinfectionsandsusceptibilitytoreinfectionhavenotbeen investigatedthusfar. If they
Even though it is not possible to investigate SARS‐CoV‐2 reinfections yet, the seasonal
infections. However, aside from being etiological agents of common cold, the four viruses are
biologically dissimilar. Two belong to the genus Alphacoronavirus, and two to the genus
Betacoronavirus.The virusesuse characteristicreceptormoleculestoentera targetcell,andbased
variability,theseasonalcoronavirusesarethemostrepresentativeviru sgroupfr omwhichtoco nclude
and susceptibility to reinfection. Since most people experience their first seasonal coronavirus
infection and—importantly—remain constant after unsuccessful viral challenge (1), increased
as the target antigen in ELISA, as this protein is immunogenic, relatively low in interspecies
Fromaprospectivecohortstudyfollowingadultmales(seeM&Mand (11)), ten subjects were
randoml yselected.Foll ow‐upof subject sstartedin1985 and,besidesagapinfollowupbetween1997
years; by the end of follow‐up , subjects were 49 to 66 years old.Thestudywasapprovedbythe
MedicalEthicsCommitteeoftheAmsterdamUniversityMedicalCenter of the University of
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Infections by seasonal coronaviruses were defined as 1.4‐fold increase in antibody levels
occurringbetweentwovisits(1),andadditionallythestandard deviationsofthemeanatbothvisits
person‐yearsof follow‐upwas15.3 (95%CI10.0‐23.4);20.1(95% CI14.2‐28.7);16.4(95%CI 10.4‐
test whether serological infection criteria represented symptomatic infections , we compared self‐
reported influenza like illnesses in the interval directly preceding the antibody peaks. Indeed,
Subject Year Age
Start End Start End Months Years Total* NL63 229E HKU1 OC43
1 1985 2017 32 64 265 22.1 14 4 3 1 6
2 1985 2019 30 64 310 25.9 15 5 6 3 1
3 1985 2020 29 64 340 28.3 6 2 3 0 1
4 1985 2010 33 59 230 19.2 22 3 12 2 5
5 1985 2010 27 53 232 19.3 9 5 3 1 0
6 1985 1997 37 49 144 12.0 3 1 1 0 1
7 1985 2003 32 49 138 11.5 13 3 5 1 4
8 1986 2014 34 62 256 21.3 10 3 5 0 2
9 1985 2010 40 75 342 28.6 22 7 5 3 7
10 1985 2011 35 60 233 19.4 18 4 6 2 6
Total  2473 205.6 132 37 49 13 33
was 12 months. For reinfections occurring as early as 6 months, we observed no reduction in
antibodies between infections (Fig. 1A, white circles). At longer infection intervals, intermediate
Theability todetect short‐termreinfectionsislimitedbythesamplinginterval.Importantly
though,noreinfectionwasobservedatthefirstsubsequentfollow‐upvisitaftera 3monthinterval
that reinfections within 6 month s do not occur. To further support this point, weexamined ratios
only ratios below 1 were found in the observations with every 3monthsampling,andwecan
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Figure1Infectionandreinfectioncharacteristics,andwaningimmunity for seasonal coronaviruses.(A) The
intervaldurationsbetweenreinfections.Onlyreinfectionswhich were observed within a continuous follow‐u p
observed. Black vertical lines describe median reinfection times. (B) Changes in antib ody levels post‐infection
relativetothefollow‐upintervalduration.Eachcirclerepresentsaninfection. Thex‐axisdescribesthetimeuntil
thenext follow‐upvisit post‐infection.The y‐axisdescribesthechange inantibody levelatthesubsequentvisit.
Largercircles representsahigherratio‐riseinantibodylevelsattheinitialinfection.Thehorizontallineindicates
curve showing decline of antibodies post infe ction (100%, 75% and 50%). The visit at which the infection wa s
establishedwas countedas timepoint0,caseswere subsequentlyfollowed. Anevent isdefinedwhen antibody
levels drop below the indicated level. When the antibody level did not decrease to the indicated levels, an
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ledtofalselabelingofinfections. We observed no significant simultaneous infections for
however, we did see that infections by the betacoronaviruses HCoV‐OC43 and HCoV‐HKU1 often
coincided (38.5%, Table 2).Likewise,foralphacoronaviruses,HCoV‐229Einfectionscoincided with
thatweoverestimated the numberinfectionsandthus reinfections. We thereforere‐analyzedthe
bya BetacoronavirusorAlphacoronavirusatagiventimepoint.Underthisdefinitionwestillfound
intervals as short as 6 months and frequent reinfections at 12 months, although the number of
Infection HCoV‐NL63 HCoV‐229E HCoV‐OC43 HCoV‐HKU1
HCoV‐NL63 NA 44.9 3.0 7.7
HCoV‐229E 59.5 NA 18.2 23.1
HCoV‐OC43 2.7 12.2 NA 38.5
HCoV‐HKU1 2.7 6.1 15.2 NA
Broadly acting antibodies recognizing SARS‐CoV‐2. In theory, antibodies induced by (repeated)
coronavirus infections may have broad coronavirus‐recognizing characteristics. We therefore
2, to allow detection of broadly reacting antibodies. Visual inspection suggested that broadly
recognizing antibodies wer e produced, and were most likely induced by combined infections with
To date it is uncertain whether SARS‐CoV‐2 will share the same winter prevalence peak that is
thatwinterpreferenceof seasonal coronaviruses has only beendetermined by testingrespiratory
symptomsandnotbystudyprotocol.Ifco ronavirusspreadcontinuesunabatedinsummer,yetpeople
rarely display symptoms (e.g. because of higher vita min D levels) and are therefore not sampl ed,
TheNetherlandshas a typicaltemperateclimate,andour study samples werecollectedatregular
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Fig.2Seasonalityofinfections.Theprevalenceof thefour seasonal coronavirusesshown as theprobability of infection
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Weshow,forthefirsttime,thatreinfectionswithallseasonal coronaviruses occur in nature.The
inthefuture,asimilarpatternmaybeexpected.However,thistimespanbetweeninfectionsdoesno t
indicatethatan individual’sprotectiveimmunitylastsforthesameperiodoftime,asreinfectionis
ofantibodywaningthatweobserved,theprotectiveimmunity maylast aslittle as6 to12 months.
Recently Kissler et al.modeledthe protective immunity andreinfectiondynamicsHCoV‐OC43 and
HCoV‐HKU1 and estimated a 45 week period of protective immunity(13).Ourserologicalstudy
use if that infection has occurred >1 year prior to sampling. Additionally, vaccine studies should
anticipate that sustained protective immunity may be uncertain for coronaviruses, and repeated
occurswhenathresholdproportion ofapopulation isimmunetoacertainpathogen,andprotects
evennon‐immune individuals against theinfectionbylimitingoverall spread. This effect has been
suchashepatitisAvirus(14),influenzaAvirus(15), andhuman papillomavirus(16).Inthecaseof
whichwouldallowthemtorelaxsocialdistancingmeasuresandprovide governmentswith dataon
herdimmunitylevels inthepopulation. However,asprotective immunitymaybelostby6 months
post infection, the prospe ct of reaching functional herd immunity by natural infection seems very
It is generally assumed that exposure to each seasonal coronavirus is not equal. The
BetacoronavirusHCoV‐HKU1is consideredtohave thelowestprevalence (4,13)andwefoundthe
same. We also observed that antibody levels to HCoV‐HKU1 were low over the whole range (all
intriguing,yetnot answerableinourstudy. Weuseda relativelysmallpartoftheNproteinasthe
WenoticedthreesubjectstocarryantibodiesrecognizingSARSCoV‐2N protein atcertain
1992(subject2),or 2006(subject 9),and wethereforesuggestthatbroadly actingantibodiesmay
havebee ninduce dbycoin cidin ginfect ionsofanAlpha‐andaBetacoronavirus(inoursub ject(s) HCoV
HKU1andHCoV‐NL63).Toexplorethisfindingwelookedat thegenetic distanceandconsequently
aminoacid differencesinthestructuralproteinofthevariouscoronaviruses(supplementaryTable
andHCoV‐229Erespectively. Similarly,thedistancebetweenAlphacoronavirusandBetacoronavirus
Nproteinislarge (only 24% to26%aminoacid identity). Still, we cannot exclude the presenceof
conserved(conformational) epitopesin HCoV‐HKU1andHCoV‐NL63 Nproteinthat mayresultin a
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more broadly acting antibody response, due to simultaneous exposure in concurrent infections.
In conclusion, seasonal human coronaviruses have little in common, apart from causing
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25. P.Mo,XingY,XiaoY,DengL,ZhaoQ,WangH,XiongY,ChengZ,GaoS,LiangK,LuoM,Chen
26. L.vanderHoek,SureK,IhorstG,StangA,PyrcK,JebbinkMF,PetersenG,ForsterJ,Berkhout
the Public Health Service of Amsterdam, the Amsterdam UMC of the University of Amsterdam, Sanquin B lood Supply
Foundation,MedicalCenter JanvanGoyen, andthe HIVFocusCenteroftheDC‐Clinics.ItispartoftheNetherlandsHIV
MonitoringFoundation andfinanciallysupportedbytheCenterforInfectiousDiseaseControlof theNetherlandsNational
ACS study nurses, data‐managers, and lab technicians. This work was supported by a grant from the European Union's
Authorcontributions:A.W.D.E:Conceptualization,Writing– originaldraft,review andediting,Investigation,Visualization,
Formal Analysis, Validation;  J.K.: Investigation, Writing  – original draft, review and editing, A.C.R.H.: Resources; M.B.:
Investigation,Resources;M.K.: Investigation;M.F.J.: Investigation,Methodology;A.M.: FormalAnalysis;C.M.K.:Writing–
originaldraft,reviewandediting,FormalAnalysis; P.R.:Resources; M.P.:Resources;P.S.: Resources;M.D.:Investigation,
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... In this Articlewe assume that onebout of infection renders a [12]; on the other hand, a very recent study [13]based on monitoring of a huge patient cohort has found demonstrable evidence of long-lasting and effective antibodies. Another study [14]on benign coronaviruses (NOT COVID-19 virus) has found an immunity period approximating one year. If N be the initial number of susceptible people (and yis of course the cumulative number of cases), then the probability that a random person is a recovered case is approximately y/N and the probability that s/he is susceptible is (approximately) 1-y/N. ...
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In this work we propose the retarded logistic equation as a dynamic model for the spread of COVID-19 all over the world. This equation accounts for asymptomatic transmission, pre-symptomatic or latent transmission as well as contact tracing and isolation, and leads to a transparent definition of the instantaneous reproduction numberR. For different parameter values, the model equation admits different classes of solutions.These solution classes correspond to, inter alia, containment of the outbreak via public health interventions, exponential growth despite interventions, containment despite reopening and second wave following reopening. We believe that the spread of COVID in every localized area such as a city, district or county can be accounted for by one of our solution classes. In regions where R>1 initially despiteaggressive epidemic managementefforts, we find that if the mitigation measures are sustained,then it is still possible for Rto dip below unity when far less than the region's entire population is affected, and from that point onwards the outbreak can be driven to extinction in time. We call this phenomenonpartial herd immunity. Our analysis indicates that the trajectory of COVID-19 in any region is extremely sensitive to small changes in the parameter values.
... In the absence of evidence of antagonistic pleiotropy, we treat this rate as consistent across strains. For SARS-coronaviruses, there is limited evidence of lifelong immunity, although some degree of at least temporary immunity appears likely [37,45,59]. We recognize that over epidemiological timescales, SARS-CoV-2 outbreak data can be accurately described by susceptible-exposed-infectiousresistant-susceptible (SEIRS)-type models. ...
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Controlling many infectious diseases, including SARS-Coronavirus-2 (SARS-CoV-2), requires surveillance followed by isolation, contact-tracing and quarantining. These interventions often begin by identifying symptomatic individuals. However, actively removing pathogen strains causing symptomatic infections may inadvertently select for strains less likely to cause symptomatic infections. Moreover, a pathogen’s fitness landscape is structured around a heterogeneous host pool; uneven surveillance efforts and distinct transmission risks across host classes can meaningfully alter selection pressures. Here, we explore this interplay between evolution caused by disease control efforts and the evolutionary consequences of host heterogeneity. Using an evolutionary epidemiology model parameterized for coronaviruses, we show that intense symptoms-driven disease control selects for asymptomatic strains, particularly when these efforts are applied unevenly across host groups. Under these conditions, increasing quarantine efforts have diverging effects. If isolation alone cannot eradicate, intensive quarantine efforts combined with uneven detections of asymptomatic infections (e.g., via neglect of some host classes) can favor the evolution of asymptomatic strains. We further show how, when intervention intensity depends on the prevalence of symptomatic infections, higher removal efforts (and isolating symptomatic cases in particular) more readily select for asymptomatic strains than when these efforts do not depend on prevalence. The selection pressures on pathogens caused by isolation and quarantining likely lie between the extremes of no intervention and thoroughly successful eradication. Thus, analyzing how different public health responses can select for asymptomatic pathogen strains is critical for identifying disease suppression efforts that can effectively manage emerging infectious diseases.
... There is a concern that, vaccination may not induce lifelong immunity as with the natural infection and re-infection may be observed. Disappointedly, vaccines for SARS-CoV and MERS-CoV raised some safety concern related to Th2 mediated immunopathology in animal studies (Edridge et al., 2020;Roper and Rehm, 2009). ...
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The outbreak of COVID-19 was recognized in December 2019 in China and as of October5th, the pandemic was swept through 216 countries and infected around 34,824,108 individuals, thus posing an unprecedented threat to world's health and economy. Several researchers reported that, a significant mutation in membrane proteins and receptor binding sites of preceding severe acute respiratory syndrome coronavirus (SARS-CoV) to turned as novel SARS-CoV-2 virus and disease was named as COVID-19 (Coronavirus disease 2019). Unfortunately, there is no specific treatment available for COVID-19 patients. The lessons learned from the past management of SARS-CoV and other pandemics, have provided some insights to treat COVID-19. Currently, therapies like anti-viral treatment, immunomodulatory agents, plasma transfusion and supportive intervention etc., are using to treat the COVID-19. Few of these were proven to provide significant therapeutic benefits in treating the COVID-19, however no drug is approved by the regulatory agencies. As the fatality rate is high in patients with comorbid conditions, we have also enlightened the current in-line treatment therapies and specific treatment strategies in comorbid conditions to combat the emergence of COVID-19. In addition, pharmaceutical, biological companies and research institutions across the globe have begun to develop thesafe and effective vaccine for COVID-19. Globally around 170 teams of researchers are racing to develop the COVID-19 vaccine and here we have discussed about their current status of development. Furthermore, recent patents filed in association with COVID-19 was elaborated. This can help many individuals, researchers or health workers, in applying these principles for diagnosis/prevention/management/treatment of the current pandemic.
... Here, we show that GX-19 induces potent antigen-specific CD4 + and CD8 + T cell activation and robust release of immune-modulatory cytokines in mice and NHPs, indicating that GX-19 can effectively control the disease of SARS-CoV-2. Therefore, clinical cases in which antibody responses rapidly decrease and disappear after SARS-CoV-2 infection indicate the importance of vaccines that can induce long-term immunological memory [48][49][50]. GX-19 induced potent CD4 + and CD8 + T cells in both animal models and it may confer long-lasting immunity against coronaviruses as indicated in SARS survivors, where CD8 + T cell immunity persisted up to 11 years [44,51]. We observed the protective benefits against viral infection about 10 weeks after the last vaccination, along with an elevated antibody response 8 weeks after the last vaccination. ...
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The unprecedented and rapid spread of SARS-CoV-2 (severe acute respiratory syndrome-coronavirus-2) has motivated the need for a rapidly producible and scalable vaccine. Here, we developed a synthetic soluble SARS-CoV-2 spike (S) DNA-based vaccine candidate, GX-19. In mice, immunization with GX-19 elicited not only S-specific systemic and pulmonary antibody responses but also Th1-biased T cell responses in a dose-dependent manner. GX-19-vaccinated nonhuman primates seroconverted rapidly and exhibited a detectable neutralizing antibody response as well as multifunctional CD4+ and CD8+ T cell responses. Notably, when the immunized nonhuman primates were challenged at 10 weeks after the last vaccination with GX-19, they had reduced viral loads in contrast to non-vaccinated primates as a control. These findings indicate that GX-19 vaccination provides a durable protective immune response and also support further development of GX-19 as a vaccine candidate for SARS-CoV-2.
... However, more knowledge on the contribution of neutralizing antibodies to protection against future infections is needed. A study that investigated antibody response and immunity to the well-known seasonal coronaviruses HCoV-NL63, HCoV-229E, HCoV-OC43, and HCoV-HKU1 has shown substantial reduction of antibodies as soon as 6 months post-infection and frequent reinfections 12 months post-infection [22]. Moreover, there is much debate on the possibility of waning immunity, with a growing amount of evidence of a decline in neutralizing antibodies [20,23,24]. ...
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A variety of serological tests have been developed to detect the presence of antibodies against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We evaluated the performance of 18 commercially available SARS-CoV-2 antibody assays. Early (6–8 days after the start of symptoms) and late sera (>14 days) from ICU patients (n=10 and n=16, respectively) and healthcare workers (n=5 and n=9, respectively) were included. Additionally, 22 sera were included to detect potential cross-reactivity. Test characteristics were determined for the 18 assays. In >14 days samples, the Vircell IgG and Wantai Ig ELISAs had superior sensitivity compared to the other ELISAs (96%). Furthermore, the Roche Ig, the Epitope Diagnostics IgM, Wantai IgM, Euroimmun IgG, and IgA all showed a specificity of 100%. The POCTs of Boson Biotech and ACRO Biotech showed the highest sensitivities: 100% and 96% (83.5–99.8), respectively. The POCT of Orient Gene Biotech, VOMED Diagnostics, and Coris-Bioconcept showed highest specificities (100%). For the IgM and IgA assays, the Euroimmun IgA test showed the highest sensitivity in early samples: 46.7% (23.5–70.9) to 53.3% (29.1–76.5). In general, all tests performed better in patients with severe symptoms (ICU patients). We conclude that the Wantai Ig and Vircell IgG ELISAs may be suitable for diagnostic purposes. The IgM/IgA tests performed poorer than their IgG/Ig counterparts but may have a role in diagnoses of SARS-CoV-2 in a population in which the background seroprevalence of IgG high, and IgM and/or IgA may distinguish between acute or past infection.
In classical viral infections, the avidity of IgG is low during acute infection and high a few months later. As recently reported, SARS-CoV-2 infections are not following this scheme, but they are rather characterized by incomplete avidity maturation. This study was performed to clarify whether infection with seasonal coronaviruses also leads to incomplete avidity maturation. The avidity of IgG towards the nucleoprotein (NP) of the seasonal coronaviruses 229E, NL63, OC43, HKU1 and of SARS-CoV-2 was determined in the sera from 88 healthy, SARS-CoV-2-negative subjects and in the sera from 70 COVID-19 outpatients, using the recomLineSARS-CoV-2 assay with recombinant antigens. In the sera from SARS-CoV-2-negative subjects, incomplete avidity maturation (persistent low and intermediate avidity indices) was the lowest for infections with the alpha-coronaviruses 229E (33.3 %) and NL63 (61.3 %), and the highest for the beta-coronaviruses OC43 (77.5%) and HKU1 (71.4%). In the sera from COVID-19 patients, the degree of incomplete avidity maturation of IgG towards NP of 223E, OC43 and HKU1 was not significantly different from that found in SARS-CoV-2-negative subjects, but a significant increase in avidity was observed for IgG towards NP of NL63. Though there was no cross-reaction between SARS-CoV-2 and seasonal coronaviruses, higher concentrations of IgG directed towards seasonal coronaviruses seemed to indirectly increase avidity maturation of IgG directed towards SARS-CoV-2. Our data show that incomplete IgG avidity maturation represents a characteristic consequence of coronavirus infections. This raises problems for the serological differentiation between acute and past infections, and may be important for the biology of coronaviruses. This article is protected by copyright. All rights reserved.
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Avidity is defined as the binding strength of IgG towards its target epitope. Avidity is directly related to affinity, as both processes are determined by the best fit of IgG to epitopes. We confirm and extend data on incomplete avidity maturation of IgG towards SARS-CoV-2 nucleoprotein (NP), spike protein-1 (S1) and its receptor-binding domain (RBD) in COVID-19 patients. In SARS-CoV-2-infected individuals, an initial rise in avidity maturation was ending abruptly, leading to IgG of persistently low or intermediate avidity. Incomplete avidity maturation might facilitate secondary SARS-CoV-2 infections and thus prevent the establishment of herd immunity. Incomplete avidity maturation after infection with SARS-CoV-2 (with only 11.8 % of cases showing finally IgG of high avidity, i. e. an avidity index > 0.6) was contrasted by regular and rapid establishment of high avidity in SARS-CoV-2 naïve individuals after two vaccination steps with the BioNTech mRNA Vaccine (78 % of cases with high avidity). One vaccination step was not sufficient for induction of complete avidity maturation in vaccinated SARS-CoV-2 naïve individuals, as it induced high avidity only in 2.9 % of cases within 3 weeks. However, one vaccination step was sufficient to induce high avidity in individuals with a previous SARS-CoV-2 infection. This article is protected by copyright. All rights reserved.
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SARS-CoV-2 emerged in late 2019 and has since spread around the world, causing a pandemic of the respiratory disease COVID-19. Detecting antibodies against the virus is an essential tool for tracking infections and developing vaccines. Such tests, primarily utilizing the enzyme-linked immunosorbent assay (ELISA) principle, can be either qualitative (reporting positive/negative results) or quantitative (reporting a value representing the quantity of specific antibodies). Quantitation is vital for determining stability or decline of antibody titers in convalescence, efficacy of different vaccination regimens, and detection of asymptomatic infections. Quantitation typically requires two-step ELISA testing, in which samples are first screened in a qualitative assay and positive samples are subsequently analyzed as a dilution series. To overcome the throughput limitations of this approach, we developed a simpler and faster system that is highly automatable and achieves quantitation in a single-dilution screening format with sensitivity and specificity comparable to those of ELISA.
Face coverings have been shown to slow the spread of COVID-19, yet their use is not universal and remains controversial in the United States. Designing effective nudges for widespread adoption is important when federal mandates are politically or legally infeasible. We report the results from a survey experiment in which subjects were exposed to one of three video messages from President Trump, and then indicated their preference for wearing a mask. In the first video, the President simply recited the Centers for Disease Control and Prevention (CDC) guidelines. In the second, the President additionally emphasized that wearing a mask is optional. In the third video, the President added that he will not personally wear a mask. We find that exposure to presidential messages can increase the stated likelihood of wearing a mask—particularly among the President’s supporters. We also explore experiential effects of COVID-19, and find that people (especially supporters of the President) are more likely to support wearing a mask if they know someone who has tested positive for COVID-19. These results offer guidance to policy makers and practitioners interested in understanding the factors that influence viral risk mitigation strategies.
The novel COVID-19 pandemic is a current, major global health threat. Up till now, there is no fully approved pharmacological treatment or a vaccine. Also, its origin is still mysterious. In this study, simple mathematical models were employed to examine the dynamics of transmission and control of COVID-19 taking into consideration social distancing and community awareness. Both situations of homogeneous and nonhomogeneous population were considered. Based on the calculations, a sufficient degree of social distancing based on its reproductive ratio is found to be effective in controlling COVID-19, even in the absence of a vaccine. With a vaccine, social distancing minimizes the sufficient vaccination rate to control the disease. Community awareness also has a great impact in eradicating the virus transmission. The model is simulated on small-world networks and the role of social distancing in controlling the infection is explained.
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What happens next? Four months into the severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) outbreak, we still do not know enough about postrecovery immune protection and environmental and seasonal influences on transmission to predict transmission dynamics accurately. However, we do know that humans are seasonally afflicted by other, less severe coronaviruses. Kissler et al. used existing data to build a deterministic model of multiyear interactions between existing coronaviruses, with a focus on the United States, and used this to project the potential epidemic dynamics and pressures on critical care capacity over the next 5 years. The long-term dynamics of SARS-CoV-2 strongly depends on immune responses and immune cross-reactions between the coronaviruses, as well as the timing of introduction of the new virus into a population. One scenario is that a resurgence in SARS-CoV-2 could occur as far into the future as 2025. Science , this issue p. 860
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In 2008, a national human papillonnavirus (HPV) immunization program using a bivalent vaccine against HPV types 16 and 18 was implemented in Scotland along with a national surveillance program designed to determine the longitudinal effects of vaccination on HPV infection at the population level. Each year during 2009-2013, the surveillance program conducted HPV testing on a proportion of liquid-based cytology samples from women undergoing their first cervical screening test for precancerous cervical disease. By linking vaccination, cervical screening, and HPV testing data, over the study period we found a decline in HPV types 16 and 18, significant decreases in HPV types 31, 33, and 45 (suggesting cross-protection), and a nonsignificant increase in HPV 51. In addition, among nonvaccinated women, HPV types 16 and 18 infections were significantly lower in 2013 than in 2009. Our results preliminarily indicate herd immunity and sustained effectiveness of the bivalent vaccine on virologic outcomes at the population level.
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Non-severe acute respiratory syndrome (non-SARS)-related human coronaviruses (HCoVs), including HCoV-229E, -HKU1, -NL63, and -OC43, have been detected in respiratory tract samples from children and adults. However, the natural prevalence of antibodies against these viruses in serum among population is unknown. To measure antibodies to the spike (S) protein of the four common non-SARS HCoVs, recombinant S proteins of the four HCoVs were expressed and characterised in 293 T cell. An S-protein-based indirect immunofluorescence assay (IFA) was then developed to detect anti-S IgG and IgM for the four individual HCoVs and applied to serum samples from a general asymptomatic population (218 children and 576 adults) in Beijing. Of 794 blood samples tested, only 29 (3.65%) were negative for anti-S IgG. The seropositivity of the four anti-S IgG antibodies was >70% within the general population. The majority of seroconversions to four-HCoV positivity first occurred in children. Both S-IgG and S-IgM antibodies were detectable among children and increased with age, reaching a plateau at 6 years of age. However, no anti-S IgM was detected in healthy adults. Large proportions of children and adults in Beijing have evidence of anti-S IgG against four the HCoVs, and first infections by all four non-SARS HCoVs takes place during childhood.
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Seasonal influenza is a significant public health concern in the United States and globally. While influenza vaccines are the single most effective intervention to reduce influenza morbidity and mortality, there is considerable debate surrounding the merits and consequences of repeated seasonal vaccination. Here, we describe a two-season influenza epidemic contact network model and use it to demonstrate that increasing the level of continuity in vaccination across seasons reduces the burden on public health. We show that revaccination reduces the influenza attack rate not only because it reduces the overall number of susceptible individuals, but also because it better protects highly-connected individuals, who would otherwise make a disproportionately large contribution to influenza transmission. Our work thus contributes a population-level perspective to debates about the merits of repeated influenza vaccination and advocates for public health policy to incorporate individual vaccine histories.
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Human coronavirus 229E has been identified in the mid-1960s, yet still only one full-genome sequence is available. This full-length sequence has been determined from the cDNA-clone Inf-1 that is based on the lab-adapted strain VR-740. Lab-adaptation might have resulted in genomic changes, due to insufficient pressure to maintain gene integrity of non-essential genes. We present here the first full-length genome sequence of two clinical isolates. Each encoded gene was compared to Inf-1. In general, little sequence changes were noted, most could be attributed to genetic drift, since the clinical isolates originate from 2009 to 2010 and VR740 from 1962. Hot spots of substitutions were situated in the S1 region of the Spike, the nucleocapsid gene, and the non-structural protein 3 gene, whereas several deletions were detected in the 3'UTR. Most notable was the difference in genome organization: instead of an ORF4A and ORF4B, an intact ORF4 was present in clinical isolates.
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Although human coronavirus OC43-OC43 (HCoV-OC43) is the coronavirus most commonly associated with human infections, little is known about its molecular epidemiology and evolution. We conducted a molecular epidemiology study to investigate different genotypes and potential recombination in HCoV-OC43. Twenty-nine HCoV-OC43 strains from nasopharyngeal aspirates, collected from 2004 to 2011, were subjected to RNA-dependent RNA polymerase (RdRp), spike, and nucleocapsid gene analysis. Phylogenetic analysis showed at least three distinct clusters of HCoV-OC43, although 10 unusual strains displayed incongruent phylogenetic positions between RdRp and spike genes. This suggested the presence of four HCoV-OC43 genotypes (A to D), with genotype D most likely arising from recombination. The complete genome sequencing of two genotype C and D strains and bootscan analysis showed recombination events between genotypes B and C in the generation of genotype D. Of the 29 strains, none belonged to the more ancient genotype A, 5 from 2004 belonged to genotype B, 15 from 2004 to 2006 belonged to genotype C, and 1 from 2004 and all 8 from 2008 to 2011 belonged to the recombinant genotype D. Molecular clock analysis using spike and nucleocapsid genes dated the most recent common ancestor of all genotypes to the 1950s, genotype B and C to the 1980s, genotype B to the 1990s, and genotype C to the late 1990s to early 2000s, while the recombinant genotype D strains were detected as early as 2004. This represents the first study to describe natural recombination in HCoV-OC43 and the evolution of different genotypes over time, leading to the emergence of novel genotype D, which is associated with pneumonia in our elderly population.
Background: Since December 2019, novel coronavirus (SARS-CoV-2)-infected pneumonia (COVID-19) occurred in Wuhan, and rapidly spread throughout China. This study aimed to clarify the characteristics of patients with refractory COVID-19. Methods: In this retrospective single-center study, we included 155 consecutive patients with confirmed COVID-19 in Zhongnan Hospital of Wuhan University from January 1st to February 5th. The cases were divided into general and refractory COVID-19 groups according to the clinical efficacy after hospitalization, and the difference between groups were compared. Results: Compared with general COVID-19 patients (45.2%), refractory patients had an older age, male sex, more underlying comorbidities, lower incidence of fever, higher levels of maximum temperature among fever cases, higher incidence of breath shortness and anorexia, severer disease assessment on admission, high levels of neutrophil, aspartate aminotransferase (AST), lactate dehydrogenase (LDH) and C-reactive protein, lower levels of platelets and albumin, and higher incidence of bilateral pneumonia and pleural effusion (P<0.05). Refractory COVID-19 patients were more likely to receive oxygen, mechanical ventilation, expectorant, and adjunctive treatment including corticosteroid, antiviral drugs and immune enhancer (P<0.05). After adjustment, those with refractory COVID-19 were also more likely to have a male sex and manifestations of anorexia and fever on admission, and receive oxygen, expectorant and adjunctive agents (P<0.05) when considering the factors of disease severity on admission, mechanical ventilation, and ICU transfer. Conclusion: Nearly 50% COVID-19 patients could not reach obvious clinical and radiological remission within 10 days after hospitalization. The patients with male sex, anorexia and no fever on admission predicted poor efficacy.
Objectives: We investigated changes in incidence rates of HIV and sexually transmitted infections (STI) and trends in sexual behavior in MSM from 2009-2017. Design: Open prospective cohort study. Methods: HIV-negative MSM enrolled in the Amsterdam Cohort Studies were included. Participants semiannually completed a questionnaire on sexual behavior and were tested for HIV-1, syphilis, and urethral, anal and pharyngeal chlamydia and gonorrhea. Time trends in incidence rates were analyzed using exponential survival models. Results: During follow-up, 42 of 905 MSM acquired HIV. The HIV incidence rate was 1.9/100 person-years (PY) (95%-confidence interval (CI) 1.0-3.7) in 2009 and decreased to 0.5/100 PY (95%-CI 0.2-1.4) in 2017 (p = 0.03). The largest decrease was observed in participants aged ≥35 years (p = 0.005), while the trend remained stable in 18-34 year olds (p = 0.4). The incidence rate for any bacterial STI was 16.8/100 PY (95%-CI 13.4-21.0) in 2010, and increased to 33.1/100 PY (95%-CI 29.0-37.9) in 2017 (p < 0.001). Between 2009-2017, the percentage reporting condomless anal sex (CAS) with casual partners increased from 26.9% to 39.4% (p < 0.001), and the mean number of casual partners from 8 (95%-CI 8-8) to 11 (95%-CI 10-11) (p = 0.05). CAS with steady partner(s) remained stable over time (p = 0.5). Conclusions: Among MSM in Amsterdam, incidence rates of HIV versus other STI show diverging trends. The increase in STI incidence coincides with a decrease in condom use with casual partners. The decrease in HIV incidence, despite increased sexual risk behavior, suggests that other HIV prevention methods have been successful in reducing HIV transmission among MSM.
A high seroprevalence of hepatitis A virus (81%) among HIV negative high risk men who have sex with men is likely why this community was largely spared from a recent HAV outbreak in San Diego, CA.
It is unknown to what extent the human coronaviruses (HCoVs) OC43, HKU1, 229E and NL63 infect healthy children. Frequencies of infections are only known for hospitalized children. Comparing infection frequencies in children who have mild infections with frequencies in children needing hospital uptake will determine whether infection by one of the four HCoVs leads to more severe disease. In addition, the sequence of seroconversions can reveal whether infection by one HCoV protects from infection by other HCoVs. Two distinct study groups were monitored: healthy children and children hospitalized due to respiratory infection. HCoV natural infection rates in healthy children were obtained by serology in 25 newborns (followed 0-20months). The frequencies of severe HCoVs infection was determined by real time RT-PCR among 1471 hospitalized infants (<2-years old) with acute respiratory tract disease. The majority of healthy children seroconverted for HCoV-OC43 (n=19) and HCoV-NL63 (n=17), less for HCoV-HKU1 (n=9) and HCoV-229E (n=5). Notably, HCoV-HKU1 seroconversion was absent after HCoV-OC43 infection. Also HCoV-229E infection was rarely observed after HCoV-NL63 infection (1 out of 5). In the hospital 207 (14%) out of 1471 children were HCoV positive. Again we observed most infection by HCoV-OC43 (n=85) and HCoV-NL63 (n=60), followed by HCoV-HKU1 (n=47) and HCoV-229E (n=15). HCoV-NL63 and HCoV-OC43 infections occur frequently in early childhood, more often than HCoV-HKU1 or HCoV-229E infections. HCoV-OC43 and HCoV-NL63 may elicit immunity that protects from subsequent HCoV-HKU1 and HCoV-229E infection, respectively, which would explain why HCoV-OC43 and HCoV-NL63 are the most frequently infecting HCoVs. There are no indications that infection by one of the HCoVs is more pathogenic than others.