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1.
Science ; 368(6489): 401-405, 2020 04 24.
Article in English | MEDLINE | ID: mdl-32193361

ABSTRACT

Although there have been no cases of serotype 2 wild poliovirus for more than 20 years, transmission of serotype 2 vaccine-derived poliovirus (VDPV2) and associated paralytic cases in several continents represent a threat to eradication. The withdrawal of the serotype 2 component of oral poliovirus vaccine (OPV2) was implemented in April 2016 to stop VDPV2 emergence and secure eradication of all serotype 2 poliovirus. Globally, children born after this date have limited immunity to prevent transmission. Using a statistical model, we estimated the emergence date and source of VDPV2s detected between May 2016 and November 2019. Outbreak response campaigns with monovalent OPV2 are the only available method to induce immunity to prevent transmission. Yet our analysis shows that using monovalent OPV2 is generating more paralytic VDPV2 outbreaks with the potential for establishing endemic transmission. A novel OPV2, for which two candidates are currently in clinical trials, is urgently required, together with a contingency strategy if this vaccine does not materialize or perform as anticipated.


Subject(s)
Disease Eradication/methods , Disease Outbreaks/prevention & control , Global Health , Poliomyelitis/epidemiology , Poliomyelitis/etiology , Poliovirus Vaccine, Oral/adverse effects , Poliovirus/immunology , Humans , Poliomyelitis/prevention & control , Poliomyelitis/transmission , Withholding Treatment
2.
BMC Infect Dis ; 18(1): 172, 2018 04 11.
Article in English | MEDLINE | ID: mdl-29642869

ABSTRACT

BACKGROUND: Quantification of human interactions relevant to infectious disease transmission through social contact is central to predict disease dynamics, yet data from low-resource settings remain scarce. METHODS: We undertook a social contact survey in rural Uganda, whereby participants were asked to recall details about the frequency, type, and socio-demographic characteristics of any conversational encounter that lasted for ≥5 min (henceforth defined as 'contacts') during the previous day. An estimate of the number of 'casual contacts' (i.e. < 5 min) was also obtained. RESULTS: In total, 566 individuals were included in the study. On average participants reported having routine contact with 7.2 individuals (range 1-25). Children aged 5-14 years had the highest frequency of contacts and the elderly (≥65 years) the fewest (P < 0.001). A strong age-assortative pattern was seen, particularly outside the household and increasingly so for contacts occurring further away from home. Adults aged 25-64 years tended to travel more often and further than others, and males travelled more frequently than females. CONCLUSION: Our study provides detailed information on contact patterns and their spatial characteristics in an African setting. It therefore fills an important knowledge gap that will help more accurately predict transmission dynamics and the impact of control strategies in such areas.


Subject(s)
Communicable Diseases/transmission , Social Behavior , Adolescent , Adult , Aged , Child , Child, Preschool , Family Characteristics , Female , Humans , Male , Middle Aged , Rural Population , Socioeconomic Factors , Surveys and Questionnaires , Travel , Uganda , Young Adult
3.
Epidemiol Infect ; 146(6): 723-734, 2018 04.
Article in English | MEDLINE | ID: mdl-29526171

ABSTRACT

In Hong Kong, universal varicella vaccination started in July 2014. Before this, children could receive varicella vaccine via the private market. We analysed the epidemiology of varicella and zoster before universal vaccination. We estimated varicella vaccination coverage through surveys in preschool children. We estimated the burden of varicella and zoster with varicella notifications from 1999/00 to 2013/14, Accident and Emergency Department (A&E) attendance and inpatient admissions to public hospitals from 2004/05 to 2013/14. We fitted a catalytic model to serological data on antibodies against varicella-zoster virus to estimate the force of infection. We found that varicella vaccination coverage gradually increased to about 50% before programme inception. In children younger than 5 years, the annual rate of varicella notifications, varicella admission and zoster A&E attendance generally declined. The annual notification, A&E attendance and hospitalisation rate of varicella and zoster generally increased for individuals between 10 and 59 years old. Varicella serology indicated an age shift during the study period towards a higher proportion of infections in slightly older individuals, but the change was most notable before vaccine licensure. In conclusion, we observed a shift in the burden of varicella to slightly older age groups with a corresponding increase in incidence but it cannot necessarily be attributed to private market vaccine coverage alone. Increasing varicella vaccination uptake in the private market might affect varicella transmission and epidemiology, but not to the level of interrupting transmission.


Subject(s)
Chickenpox/epidemiology , Herpes Zoster/epidemiology , Herpesvirus 3, Human/immunology , Adolescent , Adult , Aged , Antibodies, Viral/blood , Chickenpox/transmission , Chickenpox Vaccine/administration & dosage , Child , Child, Preschool , Disease Notification/statistics & numerical data , Disease Transmission, Infectious , Female , Hong Kong/epidemiology , Hospitalization , Humans , Incidence , Infant , Infant, Newborn , Male , Middle Aged , Pregnancy , Surveys and Questionnaires , Vaccination Coverage , Young Adult
4.
Lancet Infect Dis ; 17(12): 1276-1284, 2017 12.
Article in English | MEDLINE | ID: mdl-29033032

ABSTRACT

BACKGROUND: In March, 2016, a flare-up of Ebola virus disease was reported in Guinea, and in response ring vaccination with the unlicensed rVSV-ZEBOV vaccine was introduced under expanded access, the first time that an Ebola vaccine has been used in an outbreak setting outside a clinical trial. Here we describe the safety of rVSV-ZEBOV candidate vaccine and operational feasibility of ring vaccination as a reactive strategy in a resource-limited rural setting. METHODS: Approval for expanded access and compassionate use was rapidly sought and obtained from relevant authorities. Vaccination teams and frozen vaccine were flown to the outbreak settings. Rings of contacts and contacts of contacts were defined and eligible individuals, who had given informed consent, were vaccinated and followed up for 21 days under good clinical practice conditions. FINDINGS: Between March 17 and April 21, 2016, 1510 individuals were vaccinated in four rings in Guinea, including 303 individuals aged between 6 years and 17 years and 307 front-line workers. It took 10 days to vaccinate the first participant following the confirmation of the first case of Ebola virus disease. No secondary cases of Ebola virus disease occurred among the vaccinees. Adverse events following vaccination were reported in 47 (17%) 6-17 year olds (all mild) and 412 (36%) adults (individuals older than 18 years; 98% were mild). Children reported fewer arthralgia events than adults (one [<1%] of 303 children vs 81 [7%] of 1207 adults). No severe vaccine-related adverse events were reported. INTERPRETATION: The results show that a ring vaccination strategy can be rapidly and safely implemented at scale in response to Ebola virus disease outbreaks in rural settings. FUNDING: WHO, Gavi, and the World Food Programme.


Subject(s)
Ebola Vaccines/immunology , Hemorrhagic Fever, Ebola/prevention & control , Vaccination/methods , Adolescent , Adult , Child , Ebola Vaccines/adverse effects , Female , Guinea/epidemiology , Health Personnel , Hemorrhagic Fever, Ebola/epidemiology , Humans , Male , Occupational Exposure , Young Adult
5.
BMC Med ; 15(1): 138, 2017 07 26.
Article in English | MEDLINE | ID: mdl-28743299

ABSTRACT

BACKGROUND: Assessments of vaccine efficacy and safety capture only the minimum information needed for regulatory approval, rather than the full public health value of vaccines. Vaccine efficacy provides a measure of proportionate disease reduction, is usually limited to etiologically confirmed disease, and focuses on the direct protection of the vaccinated individual. Herein, we propose a broader scope of methods, measures and outcomes to evaluate the effectiveness and public health impact to be considered for evidence-informed policymaking in both pre- and post-licensure stages. DISCUSSION: Pre-licensure: Regulatory concerns dictate an individually randomised clinical trial. However, some circumstances (such as the West African Ebola epidemic) may require novel designs that could be considered valid for licensure by regulatory agencies. In addition, protocol-defined analytic plans for these studies should include clinical as well as etiologically confirmed endpoints (e.g. all cause hospitalisations, pneumonias, acute gastroenteritis and others as appropriate to the vaccine target), and should include vaccine-preventable disease incidence and 'number needed to vaccinate' as outcomes. Post-licensure: There is a central role for phase IV cluster randomised clinical trials that allows for estimation of population-level vaccine impact, including indirect, total and overall effects. Dynamic models should be prioritised over static models as the constant force of infection assumed in static models will usually underestimate the effectiveness and cost-effectiveness of the immunisation programme by underestimating indirect effects. The economic impact of vaccinations should incorporate health and non-health benefits of vaccination in both the vaccinated and unvaccinated populations, thus allowing for estimation of the net social value of vaccination. CONCLUSIONS: The full benefits of vaccination reach beyond direct prevention of etiologically confirmed disease and often extend across the life course of a vaccinated person, prevent outcomes in the wider community, stabilise health systems, promote health equity, and benefit local and national economies. The degree to which vaccinations provide broad public health benefits is stronger than for other preventive and curative interventions.


Subject(s)
Outcome and Process Assessment, Health Care , Public Health , Vaccines , Cost-Benefit Analysis , Hospitalization , Humans , Immunization Programs
6.
Vaccine ; 35(4): 544-551, 2017 01 23.
Article in English | MEDLINE | ID: mdl-28024952

ABSTRACT

BACKGROUND: Declining incidence and spatial heterogeneity complicated the design of phase 3 Ebola vaccine trials during the tail of the 2013-16 Ebola virus disease (EVD) epidemic in West Africa. Mathematical models can provide forecasts of expected incidence through time and can account for both vaccine efficacy in participants and effectiveness in populations. Determining expected disease incidence was critical to calculating power and determining trial sample size. METHODS: In real-time, we fitted, forecasted, and simulated a proposed phase 3 cluster-randomized vaccine trial for a prime-boost EVD vaccine in three candidate regions in Sierra Leone. The aim was to forecast trial feasibility in these areas through time and guide study design planning. RESULTS: EVD incidence was highly variable during the epidemic, especially in the declining phase. Delays in trial start date were expected to greatly reduce the ability to discern an effect, particularly as a trial with an effective vaccine would cause the epidemic to go extinct more quickly in the vaccine arm. Real-time updates of the model allowed decision-makers to determine how trial feasibility changed with time. CONCLUSIONS: This analysis was useful for vaccine trial planning because we simulated effectiveness as well as efficacy, which is possible with a dynamic transmission model. It contributed to decisions on choice of trial location and feasibility of the trial. Transmission models should be utilised as early as possible in the design process to provide mechanistic estimates of expected incidence, with which decisions about sample size, location, timing, and feasibility can be determined.


Subject(s)
Clinical Trials, Phase III as Topic , Disease Transmission, Infectious/prevention & control , Ebola Vaccines/immunology , Hemorrhagic Fever, Ebola/epidemiology , Hemorrhagic Fever, Ebola/prevention & control , Ebola Vaccines/administration & dosage , Hemorrhagic Fever, Ebola/transmission , Humans , Incidence , Models, Statistical , Sierra Leone/epidemiology
7.
Epidemics ; 11: 14-23, 2015 Jun.
Article in English | MEDLINE | ID: mdl-25979278

ABSTRACT

The basic reproduction number R0 and the effective reproduction number R are pivotal parameters in infectious disease epidemiology, quantifying the transmission potential of an infection in a population. We estimate both parameters from 13 pre-vaccination serological data sets on varicella zoster virus (VZV) in 12 European countries and from population-based social contact surveys under the commonly made assumptions of endemic and demographic equilibrium. The fit to the serology is evaluated using the inferred effective reproduction number R as a model eligibility criterion combined with AIC as a model selection criterion. For only 2 out of 12 countries, the common choice of a constant proportionality factor is sufficient to provide a good fit to the seroprevalence data. For the other countries, an age-specific proportionality factor provides a better fit, assuming physical contacts lasting longer than 15 min are a good proxy for potential varicella transmission events. In all countries, primary infection with VZV most often occurs in early childhood, but there is substantial variation in transmission potential with R0 ranging from 2.8 in England and Wales to 7.6 in The Netherlands. Two non-parametric methods, the maximal information coefficient (MIC) and a random forest approach, are used to explain these differences in R0 in terms of relevant country-specific characteristics. Our results suggest an association with three general factors: inequality in wealth, infant vaccination coverage and child care attendance. This illustrates the need to consider fundamental differences between European countries when formulating and parameterizing infectious disease models.


Subject(s)
Chickenpox/epidemiology , Chickenpox/transmission , Endemic Diseases , Herpesvirus 3, Human , Social Behavior , Adolescent , Adult , Age Factors , Aged , Child , Child, Preschool , Europe/epidemiology , Female , Humans , Infant , Male , Middle Aged , Young Adult
8.
Epidemics ; 10: 11-5, 2015 Mar.
Article in English | MEDLINE | ID: mdl-25843375

ABSTRACT

Vaccination has been one of the most successful public health measures since the introduction of basic sanitation. Substantial mortality and morbidity reductions have been achieved via vaccination against many infections, and the list of diseases that are potentially controllable by vaccines is growing steadily. We introduce key challenges for modeling in shaping our understanding and guiding policy decisions related to vaccine preventable diseases.


Subject(s)
Communicable Disease Control/methods , Vaccines/therapeutic use , Communicable Disease Control/economics , Communicable Disease Control/statistics & numerical data , Communicable Diseases/immunology , Health Policy , Humans , Immunity, Innate , Models, Statistical , Vaccines/economics
9.
Epidemics ; 10: 78-82, 2015 Mar.
Article in English | MEDLINE | ID: mdl-25843389

ABSTRACT

Infectious disease models are both concise statements of hypotheses and powerful techniques for creating tools from hypotheses and theories. As such, they have tremendous potential for guiding data collection in experimental and observational studies, leading to more efficient testing of hypotheses and more robust study designs. In numerous instances, infectious disease models have played a key role in informing data collection, including the Garki project studying malaria, the response to the 2009 pandemic of H1N1 influenza in the United Kingdom and studies of T-cell immunodynamics in mammals. However, such synergies remain the exception rather than the rule; and a close marriage of dynamic modeling and empirical data collection is far from the norm in infectious disease research. Overcoming the challenges to using models to inform data collection has the potential to accelerate innovation and to improve practice in how we deal with infectious disease threats.


Subject(s)
Communicable Diseases/epidemiology , Data Collection/methods , Observational Studies as Topic/methods , Communicable Diseases/transmission , Epidemiologic Research Design , Humans , Models, Statistical
10.
Epidemics ; 10: 93-6, 2015 Mar.
Article in English | MEDLINE | ID: mdl-25843392

ABSTRACT

The World Health Organisation's definition of public health refers to all organized measures to prevent disease, promote health, and prolong life among the population as a whole (World Health Organization, 2014). Mathematical modelling plays an increasingly important role in helping to guide the most high impact and cost-effective means of achieving these goals. Public health programmes are usually implemented over a long period of time with broad benefits to many in the community. Clinical trials are seldom large enough to capture these effects. Observational data may be used to evaluate a programme after it is underway, but have limited value in helping to predict the future impact of a proposed policy. Furthermore, public health practitioners are often required to respond to new threats, for which there is little or no previous data on which to assess the threat. Computational and mathematical models can help to assess potential threats and impacts early in the process, and later aid in interpreting data from complex and multifactorial systems. As such, these models can be critical tools in guiding public health action. However, there are a number of challenges in achieving a successful interface between modelling and public health. Here, we discuss some of these challenges.


Subject(s)
Health Policy , Public Health , Communicable Disease Control/economics , Communicable Disease Control/methods , Communicable Diseases/economics , Communicable Diseases/epidemiology , Cost-Benefit Analysis , Humans , Models, Statistical , Public Health/economics , Public Health/methods
11.
Br J Cancer ; 112(9): 1585-93, 2015 Apr 28.
Article in English | MEDLINE | ID: mdl-25791874

ABSTRACT

BACKGROUND: Human papillomavirus (HPV) vaccination of girls will have relatively little effect on HPV-related disease in men who have sex with men (MSM). We determined HPV prevalence and risk factors in MSM to inform the potential effectiveness of vaccinating MSM. METHODS: Cross-sectional study of 522 MSM aged 18-40 attending a London sexual health clinic who completed a computer-assisted self-interview. Urine and two swabs (anal and penile/scrotal/perianal) were collected and tested using an in-house Luminex-based HPV genotyping system. RESULTS: Prevalence of DNA of the vaccine-preventable HPV types in ano-genital specimens of men was 87/511 (17.0%), 166/511 (32.5%) and 232/511 (45.4%) for the bivalent (HPV16/18), quadrivalent (HPV6/11/16/18) and nonavalent (HPV6/11/16/18/31/33/45/52/58) vaccine types, respectively. A total of 25.1% had one of the quadrivalent types, and 7.4% had 2+ types. Median age at first anal sex was 19 (IQR 17-23) and at first clinic attendance was 24 (IQR 20-27). The increase in the odds of any HPV infection per year of age was 4.7% (95% CI 1.2-8.4). CONCLUSIONS: On the basis of the current infection status, most MSM, even among a high-risk population attending a sexual health clinic, are not currently infected with the vaccine-type HPV. A targeted vaccination strategy for MSM in the UK could have substantial benefits.


Subject(s)
Homosexuality, Male/psychology , Papillomaviridae/genetics , Papillomavirus Infections/epidemiology , Papillomavirus Infections/virology , Vaccination , Adolescent , Adult , Cross-Sectional Studies , Follow-Up Studies , Health Behavior , Human Papillomavirus DNA Tests , Humans , London/epidemiology , Male , Papillomaviridae/classification , Papillomaviridae/isolation & purification , Papillomavirus Infections/prevention & control , Papillomavirus Vaccines/therapeutic use , Prevalence , Prognosis , Risk Factors , Young Adult
12.
Epidemiol Infect ; 143(6): 1119-24, 2015 Apr.
Article in English | MEDLINE | ID: mdl-25115493

ABSTRACT

The age distribution of influenza A(H5N1) cases reported during 2006-2013 varied substantially between countries. As well as underlying demographic profiles, it is possible that cross-immunity contributed to the age distribution of reported cases: seasonal influenza A(H1N1) and avian influenza A(H5N1) share the same neuraminidase subtype, N1. Using a mechanistic model, we measured the extent to which population age distribution and heterosubtypic cross-immunity could explain the observed age patterns in Cambodia, China, Egypt, Indonesia and Vietnam. Our results support experimental evidence that prior infection with H1N1 confers partial cross-immunity to H5N1, and suggest that more than 50% of spillover events did not lead to reported cases of infection as a result. We also identified age groups that have additional risk factors for influenza A(H5N1) not captured by demography or infection history.


Subject(s)
Cross Reactions/immunology , Influenza A Virus, H5N1 Subtype/immunology , Influenza, Human/immunology , Adolescent , Adult , Age Factors , Aged , Child , Child, Preschool , Global Health , Humans , Influenza A Virus, H1N1 Subtype/immunology , Influenza, Human/epidemiology , Influenza, Human/virology , Middle Aged , Risk Factors , Young Adult
14.
J Hosp Infect ; 88(4): 213-7, 2014 Dec.
Article in English | MEDLINE | ID: mdl-25441017

ABSTRACT

BACKGROUND: The burden of healthcare-associated infections, such as healthcare-acquired Clostridium difficile (HA-CDI), can be expressed in terms of additional length of stay (LOS) and mortality. However, previous estimates have varied widely. Although some have considered time of infection onset (time-dependent bias), none considered the impact of severity of HA-CDI; this was the primary aim of this study. METHODS: The daily risk of in-hospital death or discharge was modelled using a Cox proportional hazards model, fitted to data on patients discharged in 2012 from a large English teaching hospital. We treated HA-CDI status as a time-dependent variable and adjusted for confounders. In addition, a multi-state model was developed to provide a clinically intuitive metric of delayed discharge associated with non-severe and severe HA-CDI respectively. FINDINGS: Data comprised 157 (including 48 severe) HA-CDI cases among 42,618 patients. HA-CDI reduced the daily discharge rate by nearly one-quarter [hazard ratio (HR): 0.72; 95% confidence interval (CI): 0.61-0.84] and increased the in-hospital death rate by 75% compared with non-HA-CDI patients (HR: 1.75; 95% CI: 1.16-2.62). Whereas overall HA-CDI resulted in a mean excess LOS of about seven days (95% CI: 3.5-10.9), severe cases had an average excess LOS which was twice (∼11.6 days; 95% CI: 3.6-19.6) that of the non-severe cases (about five days; 95% CI: 1.1-9.5). CONCLUSION: HA-CDI contributes to patients' expected LOS and risk of mortality. However, when quantifying the health and economic burden of hospital-onset of HA-CDI, the heterogeneity in the impact of HA-CDI should be accounted for.


Subject(s)
Clostridioides difficile , Cross Infection/mortality , Enterocolitis, Pseudomembranous/mortality , Hospital Mortality , Length of Stay , Adult , Aged , Aged, 80 and over , Humans , Middle Aged , Patient Discharge , Proportional Hazards Models
15.
Epidemics ; 9: 70-8, 2014 Dec.
Article in English | MEDLINE | ID: mdl-25480136

ABSTRACT

Outbreaks of Ebola virus can cause substantial morbidity and mortality in affected regions. The largest outbreak of Ebola to date is currently underway in West Africa, with 3944 cases reported as of 5th September 2014. To develop a better understanding of Ebola transmission dynamics, we revisited data from the first known Ebola outbreak, which occurred in 1976 in Zaire (now Democratic Republic of Congo). By fitting a mathematical model to time series stratified by disease onset, outcome and source of infection, we were able to estimate several epidemiological quantities that have previously proved challenging to measure, including the contribution of hospital and community infection to transmission. We found evidence that transmission decreased considerably before the closure of the hospital, suggesting that the decline of the outbreak was most likely the result of changes in host behaviour. Our analysis suggests that the person-to-person reproduction number was 1.34 (95% CI: 0.92-2.11) in the early part of the outbreak. Using stochastic simulations we demonstrate that the same epidemiological conditions that were present in 1976 could have generated a large outbreak purely by chance. At the same time, the relatively high person-to-person basic reproduction number suggests that Ebola would have been difficult to control through hospital-based infection control measures alone.


Subject(s)
Disease Outbreaks/statistics & numerical data , Hemorrhagic Fever, Ebola/epidemiology , Algorithms , Bayes Theorem , Community-Acquired Infections/epidemiology , Cross Infection/epidemiology , Democratic Republic of the Congo/epidemiology , Hemorrhagic Fever, Ebola/transmission , Humans , Models, Statistical , Models, Theoretical
16.
Epidemiol Infect ; 140(12): 2117-30, 2012 Dec.
Article in English | MEDLINE | ID: mdl-22687447

ABSTRACT

A central tenet of close-contact or respiratory infection epidemiology is that infection patterns within human populations are related to underlying patterns of social interaction. Until recently, few researchers had attempted to quantify potentially infectious encounters made between people. Now, however, several studies have quantified social mixing behaviour, using a variety of methods. Here, we review the methodologies employed, suggest other appropriate methods and technologies, and outline future research challenges for this rapidly advancing field of research.


Subject(s)
Respiratory Tract Infections/epidemiology , Respiratory Tract Infections/transmission , Social Behavior , Social Participation , Contact Tracing , Humans , Mathematical Concepts , Radio Frequency Identification Device
17.
Med Decis Making ; 32(1): 209-20, 2012.
Article in English | MEDLINE | ID: mdl-21610256

ABSTRACT

INTRODUCTION: The best data for cost-effectiveness analyses (CEAs) of group-level interventions often come from cluster randomized trials (CRTs), where randomization is by cluster (e.g., the hospital attended), not by individual. METHODS: for these CEAs need to recognize both the correlation between costs and outcomes and that these data may be dependent on the cluster. General checklists and methodological guidance for critically appraising CEA ignore these issues. This article develops a new checklist and applies it in a systematic review of CEAs that use CRTs. METHODS: The authors developed a checklist for CEAs that use CRTs, informed by a conceptual review of statistical methods. This checklist included criteria such as whether the analysis allowed for both clustering and the correlation between individuals' costs and outcomes. The authors undertook a systematic literature review of full economic evaluations that used CRTs. The quality of studies was assessed with the new checklist and by the "Drummond checklist." RESULTS: The authors identified 62 papers that met the inclusion criteria. On average, studies satisfied 9 of the 10 criteria for the checklist but only 20% of criteria for the new checklist. More than 40% of studies adopted statistical methods that completely ignored clustering, and 75% disregarded any correlation between costs and outcomes. Only 4 studies employed appropriate statistical methods that allowed for both clustering and correlation. CONCLUSIONS: Most economic evaluations that use data from CRTs ignored clustering or correlation. Statistical methods that address these issues are available, and their use should be encouraged. The new checklist can supplement generic CEA guidelines and highlight where research practice can be improved.


Subject(s)
Checklist , Cluster Analysis , Models, Statistical , Randomized Controlled Trials as Topic/statistics & numerical data , Cost-Benefit Analysis/methods , Cost-Benefit Analysis/statistics & numerical data
18.
Epidemiol Infect ; 140(7): 1309-15, 2012 Jul.
Article in English | MEDLINE | ID: mdl-21906412

ABSTRACT

The effectiveness of influenza vaccination programmes is seldom known during an epidemic. We developed an internet-based system to record influenza-like symptoms and response to infection in a participating cohort. Using self-reports of influenza-like symptoms and of influenza vaccine history and uptake, we estimated vaccine effectiveness (VE) without the need for individuals to seek healthcare. We found that vaccination with the 2010 seasonal influenza vaccine was significantly protective against influenza-like illness (ILI) during the 2010-2011 influenza season (VE 52%, 95% CI 27-68). VE for individuals who received both the 2010 seasonal and 2009 pandemic influenza vaccines was 59% (95% CI 27-77), slightly higher than VE for those vaccinated in 2010 alone (VE 46%, 95% CI 9-68). Vaccinated individuals with ILI reported taking less time off work than unvaccinated individuals with ILI (3.4 days vs. 5.3 days, P<0.001).


Subject(s)
Influenza Vaccines/administration & dosage , Influenza Vaccines/immunology , Influenza, Human/prevention & control , Absenteeism , Adolescent , Adult , Aged, 80 and over , Child , Child, Preschool , Cohort Studies , Data Collection/methods , Female , Humans , Infant , Infant, Newborn , Influenza, Human/pathology , Internet , Male , Middle Aged , Young Adult
19.
Health Technol Assess ; 14(34): 267-312, 2010 Jul.
Article in English | MEDLINE | ID: mdl-20630125

ABSTRACT

BACKGROUND: Mathematical models, based on data describing normal patterns of social mixing, are used to understand epidemics in order to predict patterns of disease spread and plan interventions and responses. However, individuals who are ill show behavioural changes that affect their social mixing patterns and predictive models should take into account these changes if they are to be effective. OBJECTIVES: To describe and quantify the changes in (1) social contact behaviour experienced by individuals when they are ill with pandemic H1N1 influenza (swine flu) and (2) mixing patterns of school children that take place as a result of swine flu-related school closures. METHODS: For the first part of the study, a self-completed questionnaire-based study was carried out in the autumn/winter of 2009-10. The study population was individuals who had been diagnosed with swine flu and who received a swine flu antiviral prescription from an antiviral distribution centre (ADC). It consisted of an initial survey to be filled in when participants were symptomatic with swine flu and a follow-up survey to be filled in when they had recovered. Each part of the questionnaire had two sections: patient details and a contact diary. The second part of the study was adapted to quantify the difference in mixing patterns of pupils between the school term and the half-term holiday as school closures did not occur during the study period. Eight schools participated and questionnaire packs were distributed to them, containing two surveys: one to be filled in during the school term and one during the spring half-term holiday. RESULTS: For the patient study, approximately 3800 surveys were distributed by 31 ADCs. Overall, 317 responses to the initial survey were received and 179 participants returned the follow-up survey. For all types of a contact, except contacts made at home, there were highly significant differences in contact behaviour (Wilcoxon signed-rank test, p < 0.001). Individuals made substantially fewer contacts when they were ill than when they were well. Analysis showed that returning to work was the most significant predictor of increased numbers of contacts. Also, the greater the change in the number of symptoms reported, the greater the change in the number of contacts. For the school study, approximately 1100 questionnaire packs were distributed and 134 responses were received, with 119 paired contact diaries. Pupils reported on average 18.51 contacts each day during term time and 9.24 during the half-term holiday - a reduction of over 50% and a highly significant change (Wilcoxon signed-rank test, p < 0.0001). CONCLUSIONS: The evidence from this study suggests that ill individuals make substantial changes to their social contact patterns. These changes are strongly linked to absence from work and the severity of the reported illness. Epidemiological modellers should therefore consider the implications of illness-related behavioural changes on model predictions. Future studies to measure the extent of behavioural change in a broader cross-section of infected cases could be valuable, along with more detailed studies of the social contact patterns of school children, focusing on differences between school terms and school holidays.


Subject(s)
Disease Outbreaks/prevention & control , Influenza A Virus, H1N1 Subtype , Influenza, Human/psychology , Schools , Adolescent , Adult , Child , Child, Preschool , Female , Humans , Illness Behavior , Infant , Infant, Newborn , Influenza, Human/epidemiology , Influenza, Human/prevention & control , Influenza, Human/transmission , Male , Middle Aged , Sickness Impact Profile , Social Behavior , Surveys and Questionnaires , Workplace , Young Adult
20.
Sex Transm Infect ; 85(5): 359-66, 2009 Sep.
Article in English | MEDLINE | ID: mdl-19454407

ABSTRACT

BACKGROUND: Published individual-based, dynamic sexual network modelling studies reach different conclusions about the population impact of screening for Chlamydia trachomatis. The objective of this study was to conduct a direct comparison of the effect of organised chlamydia screening in different models. METHODS: Three models simulating population-level sexual behaviour, chlamydia transmission, screening and partner notification were used. Parameters describing a hypothetical annual opportunistic screening program in 16-24 year olds were standardised, whereas other parameters from the three original studies were retained. Model predictions of the change in chlamydia prevalence were compared under a range of scenarios. RESULTS: Initial overall chlamydia prevalence rates were similar in women but not men and there were age and sex-specific differences between models. The number of screening tests carried out was comparable in all models but there were large differences in the predicted impact of screening. After 10 years of screening, the predicted reduction in chlamydia prevalence in women aged 16-44 years ranged from 4% to 85%. Screening men and women had a greater impact than screening women alone in all models. There were marked differences between models in assumptions about treatment seeking and sexual behaviour before the start of the screening intervention. CONCLUSIONS: Future models of chlamydia transmission should be fitted to both incidence and prevalence data. This meta-modelling study provides essential information for explaining differences between published studies and increasing the utility of individual-based chlamydia transmission models for policy making.


Subject(s)
Chlamydia Infections/epidemiology , Forecasting/methods , Models, Theoretical , Adolescent , Adult , Chlamydia Infections/diagnosis , Chlamydia Infections/transmission , Contact Tracing , Female , Humans , Incidence , Male , Mass Screening , Netherlands/epidemiology , Prevalence , Sexual Behavior , United Kingdom/epidemiology , Young Adult
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