Household Transmission of Influenza Virus
2015; Elsevier BV; Volume: 24; Issue: 2 Linguagem: Inglês
10.1016/j.tim.2015.10.012
ISSN1878-4380
AutoresTim K. Tsang, Lincoln Lau, Simon Cauchemez, Benjamin J. Cowling,
Tópico(s)COVID-19 epidemiological studies
ResumoHistorically, household cohort studies have provided valuable information on the incidence of respiratory infections and risk factors for infection. However, these studies require substantial resources and can provide limited information on transmission dynamics. Household transmission studies provide an efficient approach to describing the risk of influenza transmission and factors affecting transmission. In these studies, households with at least one member infected by influenza are eligible and are followed intensively for 1–2 weeks to observe secondary transmission within the household. Transmission studies also provide a model for evaluation of interventions in randomized controlled trials, and have been used to determine the efficacy of antiviral drugs for treatment and prophylaxis, and nonpharmaceutical interventions such as face masks and hand hygiene. Human influenza viruses cause regular epidemics and occasional pandemics with a substantial public health burden. Household transmission studies have provided valuable information on the dynamics of influenza transmission. We reviewed published studies and found that once one household member is infected with influenza, the risk of infection in a household contact can be up to 38%, and the delay between onset in index and secondary cases is around 3 days. Younger age was associated with higher susceptibility. In the future, household transmission studies will provide information on transmission dynamics, including the correlation of virus shedding and symptoms with transmission, and the correlation of new measures of immunity with protection against infection. Human influenza viruses cause regular epidemics and occasional pandemics with a substantial public health burden. Household transmission studies have provided valuable information on the dynamics of influenza transmission. We reviewed published studies and found that once one household member is infected with influenza, the risk of infection in a household contact can be up to 38%, and the delay between onset in index and secondary cases is around 3 days. Younger age was associated with higher susceptibility. In the future, household transmission studies will provide information on transmission dynamics, including the correlation of virus shedding and symptoms with transmission, and the correlation of new measures of immunity with protection against infection. Human influenza viruses cause regular epidemics and occasional pandemics. During influenza epidemics, high attack rates of generally mild and self-limiting illnesses cause a substantial public health burden, and a small fraction of infections are severe, requiring hospitalization [1Monto A.S. Global burden of influenza: what we know and what we need to know.Int. Cong. Ser. 2004; 1263: 3-11Crossref Scopus (16) Google Scholar]. Community-based studies of influenza virus infection and transmission have provided detailed information on influenza epidemiology since the 1920s [2Monto A.S. Studies of the community and family: acute respiratory illness and infection.Epidemiol. Rev. 1994; 16: 351-373Crossref PubMed Scopus (167) Google Scholar], with a series of seminal studies in the 1950s, 1960s, and 1970s, the most comprehensive of which was the 10-year Tecumseh study of acute respiratory infections in households [3Monto A.S. Ullman B.M. Acute respiratory illness in an American community. The Tecumseh study.JAMA. 1974; 227: 164-169Crossref PubMed Scopus (343) Google Scholar, 4Monto A.S. et al.Tecumseh study of illness. XIII. Influenza infection and disease, 1976–1981.Am. J. Epidemiol. 1985; 121: 811-822Crossref PubMed Scopus (258) Google Scholar]. These studies conducted serologic and virologic testing of participants to determine the frequency of acute respiratory illnesses and identified the etiologic agents responsible. By enrolling entire households, these studies also examined transmission of respiratory pathogens, including influenza virus, identifying, for example, the importance of school-age children in introducing infections to the household [5Longini Jr, I.M. et al.Estimating household and community transmission parameters for influenza.Am. J. Epidemiol. 1982; 115: 736-751Crossref PubMed Scopus (298) Google Scholar]. More recently, an efficient study design known as the household transmission study has been increasingly used to study influenza virus transmission. During the 2009 influenza pandemic, this design was used to provide early estimates of transmission dynamics of the novel H1N1pdm09 strain, including the risk of infection among household contacts and the serial interval, defined as the time from symptom onset in the index case to the secondary case, and the severity of illnesses [6Lau L.L. et al.Household transmission of 2009 pandemic influenza A (H1N1): a systematic review and meta-analysis.Epidemiology. 2012; 23: 531-542Crossref PubMed Scopus (65) Google Scholar]. This review describes the methodology used in these transmission studies, the main findings of the studies on the transmission dynamics of human influenza viruses in households, and the potential for further research using this study design to provide answers to important outstanding questions on influenza. Household cohort studies have been used to study influenza epidemiology for many years [4Monto A.S. et al.Tecumseh study of illness. XIII. 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Participants in the study are then followed up prospectively across one or more influenza epidemic, or influenza season, to identify infections and illnesses. In many cohort studies, sera will be collected from participants before and after influenza epidemics, to permit identification of infections by, for example, the proportion of individuals with a 4-fold or greater rise in antibody titer against a particular strain across an epidemic of that strain [18Wood J.M. et al.Comparison of influenza serological techniques by international collaborative study.Vaccine. 1994; 12: 167-174Crossref PubMed Scopus (115) Google Scholar, 19Katz J.M. et al.Serologic assays for influenza surveillance, diagnosis and vaccine evaluation.Expert Rev. Anti. Infect. Ther. 2011; 9: 669-683Crossref PubMed Scopus (188) Google Scholar]. During an influenza epidemic, or in some cases throughout follow-up regardless of influenza activity, participants may keep symptom diaries to permit estimation of the incidence of acute respiratory illnesses. Collection of nasal swabs or other respiratory specimens from ill participants, or at regular intervals from all participants regardless of illness [20Fox J.P. et al.Influenzavirus infections in Seattle families, 1975–1979. I. Study design, methods and the occurrence of infections by time and age.Am. J. Epidemiol. 1982; 116: 212-227Crossref PubMed Scopus (212) Google Scholar], can permit virologic identification of specific pathogens causing those illnesses, including influenza viruses. An advantage of household studies is the efficiency of simultaneously following up multiple individuals in households rather than separately following up the same number of people independently selected from the population. Compared with other types of close contacts, household contacts are easier to identify and follow up, and they provide a well-defined number of susceptible people that are likely to have been exposed to infection, compared with other settings such as schools, offices, or hospitals. Household cohort studies can also permit inference on the transmission dynamics of influenza in households, providing valuable data on transmission in the broader community because a substantial fraction of influenza virus transmission events do occur in households [21Chao D.L. et al.FluTE, a publicly available stochastic influenza epidemic simulation model.PLoS Comput. Biol. 2010; 6: e1000656Crossref PubMed Scopus (255) Google Scholar, 22Ferguson N.M. et al.Strategies for mitigating an influenza pandemic.Nature. 2006; 442: 448-452Crossref PubMed Scopus (1654) Google Scholar]. However, in many cohort studies infections are ascertained by serologic analysis, which can have imperfect sensitivity and specificity, and only provides what is known as final size data in which the number of infected and uninfected household members is known at the end of each epidemic [5Longini Jr, I.M. et al.Estimating household and community transmission parameters for influenza.Am. J. Epidemiol. 1982; 115: 736-751Crossref PubMed Scopus (298) Google Scholar]. Specialized methods have been developed to permit inference on transmission dynamics (who was infected by whom) based on final size data, allowing for the risks of acquiring infection from outside or inside the household [5Longini Jr, I.M. et al.Estimating household and community transmission parameters for influenza.Am. J. Epidemiol. 1982; 115: 736-751Crossref PubMed Scopus (298) Google Scholar, 23Ball F. Neal P. A general model for stochastic SIR epidemics with two levels of mixing.Math. 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In addition, it is not possible to estimate the serial interval based on final size data, although this epidemiologic parameter, measuring the average time between illness onset in an infected person and a secondary case infected by that person, is an important parameter for mechanistic models (also called mathematical models) of influenza epidemics that are often used for policy planning [22Ferguson N.M. et al.Strategies for mitigating an influenza pandemic.Nature. 2006; 442: 448-452Crossref PubMed Scopus (1654) Google Scholar, 25Ferguson N.M. et al.Strategies for containing an emerging influenza pandemic in Southeast Asia.Nature. 2005; 437: 209-214Crossref PubMed Scopus (1478) Google Scholar]. Some of these limitations can be ameliorated by careful collection of respiratory specimens from ill individuals, although intense follow up for illnesses over a prolonged period is challenging and demands considerable resources [26Klick B. et al.Optimal design of studies of influenza transmission in households. II: comparison between cohort and case-ascertained studies.Epidemiol. Infect. 2014; 142: 744-752Crossref PubMed Scopus (14) Google Scholar, 27Klick B. et al.Optimal design of studies of influenza transmission in households. I: case-ascertained studies.Epidemiol. Infect. 2012; 140: 106-114Crossref PubMed Scopus (18) Google Scholar]. While cohort studies can provide valuable data on influenza and other acute respiratory illnesses, there are a number of limitations, the greatest of which is the substantial resources required to establish and follow up a cohort of hundreds or typically thousands of participants over a series of influenza epidemics. Furthermore, in areas where influenza seasons are difficult to predict, for example in tropical and subtropical regions, collecting well-timed pre-epidemic and post-epidemic sera can be difficult [7Cauchemez S. et al.Determinants of influenza transmission in South East Asia: insights from a household cohort study in Vietnam.PLoS Pathog. 2014; 10: e1004310Crossref PubMed Scopus (31) Google Scholar, 8Horby P. et al.The epidemiology of interpandemic and pandemic influenza in Vietnam, 2007-2010: the Ha Nam household cohort study I.Am. J. Epidemiol. 2012; 175: 1062-1074Crossref PubMed Scopus (72) Google Scholar, 9Riley S. et al.Epidemiological characteristics of 2009 (H1N1) pandemic influenza based on paired sera from a longitudinal community cohort study.PLoS Med. 2011; 8: e1000442Crossref PubMed Scopus (98) Google Scholar, 28Cowling B.J. et al.Incidence of influenza virus infections in children in Hong Kong in a 3-year randomized placebo-controlled vaccine study, 2009–2012.Clin. Infect. Dis. 2014; 59: 517-524Crossref PubMed Scopus (49) Google Scholar, 29Klick B. et al.Transmissibility of seasonal and pandemic influenza in a cohort of households in Hong Kong in 2009.Epidemiology. 2011; 22: 793-796PubMed Google Scholar, 30Van Kerkhove M.D. et al.Estimating age-specific cumulative incidence for the 2009 influenza pandemic: a meta-analysis of A(H1N1)pdm09 serological studies from 19 countries.Influenza Other Respir. Viruses. 2013; 7: 872-886Crossref PubMed Scopus (155) Google Scholar, 31Wu J.T. et al.Estimating infection attack rates and severity in real time during an influenza pandemic: analysis of serial cross-sectional serologic surveillance data.PLoS Med. 2011; 8: e1001103Crossref PubMed Scopus (53) Google Scholar, 32Wu J.T. et al.The infection attack rate and severity of 2009 pandemic H1N1 influenza in Hong Kong.Clin. Infect. Dis. 2010; 51: 1184-1191Crossref PubMed Scopus (165) Google Scholar], leading to difficulties in interpreting serological data. Cohort studies were established to determine the cumulative incidence of H1N1pdm09 infections in 2009, but most such studies could not be established quickly enough to collect baseline pre-epidemic sera [30Van Kerkhove M.D. et al.Estimating age-specific cumulative incidence for the 2009 influenza pandemic: a meta-analysis of A(H1N1)pdm09 serological studies from 19 countries.Influenza Other Respir. Viruses. 2013; 7: 872-886Crossref PubMed Scopus (155) Google Scholar]. Finally, as mentioned above, it is difficult to characterize heterogeneity in transmission dynamics using cohort studies. One particular study design that has been introduced to characterize the risk of transmission and heterogeneity in transmission risk is the household transmission study, also known as the case ascertained study [6Lau L.L. et al.Household transmission of 2009 pandemic influenza A (H1N1): a systematic review and meta-analysis.Epidemiology. 2012; 23: 531-542Crossref PubMed Scopus (65) Google Scholar, 33Yang Y. et al.Design and evaluation of prophylactic interventions using infectious disease incidence data from close contact groups.J. R. Stat. Soc. Ser. C: Appl. Stat. 2006; 55: 317-330Crossref PubMed Scopus (51) Google Scholar]. In a household transmission study of influenza, in contrast to a traditional cohort study as described above, households are eligible for enrolment only after at least one household member has been identified as having an acute influenza virus infection [34Viboud C. et al.Risk factors of influenza transmission in households.Br. J. Gen. Pract. 2004; 54: 684-689PubMed Google Scholar]. This case can be referred to as the index case, and the other members as household contacts, with caveats on this terminology discussed below. In contrast to cohort studies, household transmission studies typically involve a short duration of follow-up of participants for 1 or 2 weeks, or in some cases 1 month to permit collection of convalescent sera. Collection of respiratory specimens, such as nasal swabs or sera, from household contacts permits ascertainment of secondary infections in the households with laboratory confirmation, and symptom diaries provide information on illnesses. Differences between the cohort and transmission study design are illustrated in Figure 1. In principle, the transmission study is also a cohort study because it involves a defined cohort of individuals, but it differs from the traditional cohort study because only households with at least one infected person are included, and in theory the same household can be enrolled more than once (Figure 1). Further complicating the distinction, it is also possible to effectively nest a transmission study within a cohort study, by intensively observing participants in a traditional cohort study and initiating additional investigations once one household member becomes infected [35Thai P.Q. et al.Pandemic H1N1 virus transmission and shedding dynamics in index case households of a prospective Vietnamese cohort.J. Infect. 2014; 68: 581-590Abstract Full Text Full Text PDF PubMed Scopus (32) Google Scholar]. In household transmission studies, information on the dates of illness onset in index and secondary cases allows estimation of the serial interval, and identification of factors associated with heterogeneity in transmission. One caveat of this design is that the identity of the person who first introduced infection into the household can be unclear, and may not necessarily be the person enrolled in the study as the 'index case'. For example, in one household, the first infected person may have very mild illness that is not apparent, but is sufficiently infectious to transmit infection to a second person who has a more serious illness, seeks care at an outpatient clinic, and is enrolled as the index case. Finally, it should be mentioned that the definition of a household can vary between cultures. In western cultures, the household typically comprises a nuclear family, but in other cultures – and particularly in low- and middle-income countries – it is possible to find large extended families or social groups living together in compounds or small communities with substantial interactions that should not be ignored when analyzing transmission dynamics in the nuclear families. The primary objective of a typical household transmission study is an estimate of the transmissibility of influenza viruses within the household, measured by the Secondary Infection Risk (SIR), that is, the proportion of household contacts that are infected during the study period. In a basic descriptive analysis, this is simply the proportion of household contacts that develop cases of confirmed influenza virus infection, or the proportion of household contacts that develop an acute respiratory illness. The SIR has frequently been referred to as the 'secondary attack rate' in the literature [36Halloran M.E. Secondary attack rate.in: Armitage P. Colton T. Encyclopedia of Biostatistics. John Wiley and Sons, Inc, 2005: 4025-4029Crossref Google Scholar]. However, we note that infections do not necessarily cause more severe illness (attack) and the quantity in question is a risk, that is, a proportion, not an incidence rate with a person–time denominator. The term 'secondary infection risk' therefore seems preferable [6Lau L.L. et al.Household transmission of 2009 pandemic influenza A (H1N1): a systematic review and meta-analysis.Epidemiology. 2012; 23: 531-542Crossref PubMed Scopus (65) Google Scholar]. More complex statistical analyses can also be performed to take into account the potential for some contacts to acquire infection from outside the household, and other infections to be third-generation 'tertiary' cases rather than secondary cases [37Cauchemez S. et al.A Bayesian MCMC approach to study transmission of influenza: application to household longitudinal data.Stat. Med. 2004; 23: 3469-3487Crossref PubMed Scopus (284) Google Scholar]. These analyses make it possible to estimate the 'person-to-person' household transmission risk, that is, the probability of transmission from a case to a single household member. The person-to-person household transmission risk is usually lower than the SIR because of the additional risk of the household contact acquiring infection from another source apart from the index case [38Cauchemez S. et al.Household transmission of 2009 pandemic influenza A (H1N1) virus in the United States.N. Engl. J. 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Heterogeneity in transmission could occur because of (i) variation in infectiousness, for example, if infected children were more infectious than infected adults to their family members; (ii) variation in susceptibility to infection, for example, if vaccinated contacts were less likely to contract infection in the household than unvaccinated contacts; or (iii) variation in the environment, for example, households with better ventilation might experience less within-household transmission. As described in the previous section, household transmission studies can provide evidence on the serial interval, which is related to the generation time, the duration of infectiousness, and the incubation period. Serial intervals can be used to inform and characterize the speed with which an epidemic will spread, as well as the time during which people are infectious – with implications for isolation policies [43Fine P.E. The interval between successive cases of an infectious disease.Am. J. Epidemiol. 2003; 158: 1039-1047Crossref PubMed Scopus (194) Google Scholar]. Control measures can be improved by identification of important factors affecting transmissions in households. Furthermore, experiments may be conducted with this design, for example, by randomly allocating interventions to different participants or different households to determine how effectively those interventions can control transmission. One factor of particular interest is the correlation of immune status with protection against infection. We conducted a review of household transmission studies of influenza, explored the typical design and implementation of these studies, and contrasted and compared their major findings. We identified 56 relevant published studies (see Tables S1 and S2 in the supplemental information online) [34Viboud C. et al.Risk factors of influenza transmission in households.Br. J. Gen. 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