The Role of Reinfection and Partner Notification in the Efficacy of Chlamydia Screening Programs

Repeated Chlamydia trachomatis infections after treatment are common. One reason is reinfection from untreated partners in ongoing sexual partnerships. Mathematical models that are used to predict the impact of screening on reducing chlamydia prevalence often do not incorporate reinfection and might overestimate the expected impact. We describe a pair compartmental model that explicitly incorporates sexual partnership duration and reinfection. The pair model predicts a weaker impact of screening when compared directly with a model that does not accommodate partnerships. Effective management of sex partners to prevent reinfection might need to be strengthened in chlamydia control program

Sample size considerations using mathematical models: an example with Chlamydia trachomatis infection and its sequelae pelvic inflammatory disease.

BACKGROUND The success of an intervention to prevent the complications of an infection is influenced by the natural history of the infection. Assumptions about the temporal relationship between infection and the development of sequelae can affect the predicted effect size of an intervention and the sample size calculation. This study investigates how a mathematical model can be used to inform sample size calculations for a randomised controlled trial (RCT) using the example of Chlamydia trachomatis infection and pelvic inflammatory disease (PID). METHODS We used a compartmental model to imitate the structure of a published RCT. We considered three different processes for the timing of PID development, in relation to the initial C. trachomatis infection: immediate, constant throughout, or at the end of the infectious period. For each process we assumed that, of all women infected, the same fraction would develop PID in the absence of an intervention. We examined two sets of assumptions used to calculate the sample size in a published RCT that investigated the effect of chlamydia screening on PID incidence. We also investigated the influence of the natural history parameters of chlamydia on the required sample size. RESULTS The assumed event rates and effect sizes used for the sample size calculation implicitly determined the temporal relationship between chlamydia infection and PID in the model. Even small changes in the assumed PID incidence and relative risk (RR) led to considerable differences in the hypothesised mechanism of PID development. The RR and the sample size needed per group also depend on the natural history parameters of chlamydia. CONCLUSIONS Mathematical modelling helps to understand the temporal relationship between an infection and its sequelae and can show how uncertainties about natural history parameters affect sample size calculations when planning a RCT

Reinfection by untreated partners of people treated for Chlamydia trachomatis and Neisseria gonorrhoeae: mathematical modelling study

OBJECTIVES Reinfection after treatment for Chlamydia trachomatis or Neisseria gonorrhoeae reduces the effect of control interventions. We explored the impact of delays in treatment of current partners on the expected probability of reinfection of index cases using a mathematical model. METHODS We used previously reported parameter distributions to calculate the probability that index cases would be reinfected by their untreated partners. We then assumed different delays between index case and partner treatment to calculate the probabilities of reinfection. RESULTS In the absence of partner treatment, the medians of the expected reinfection probabilities are 19.4% (IQR 9.2-31.6%) for C trachomatis and 12.5% (IQR 5.6-22.2%) for N gonorrhoeae. If all current partners receive treatment 3 days after the index case, the expected reinfection probabilities are 4.2% (IQR 2.1-6.9%) for C trachomatis and 5.5% (IQR 2.6-9.5%) for N gonorrhoeae. CONCLUSIONS Quicker partner referral and treatment can substantially reduce reinfection rates for C trachomatis and N gonorrhoeae by untreated partners. The formula we used to calculate reinfection rates can be used to inform the design of randomised controlled trials of novel partner notification technologies like accelerated partner therapy

Effectiveness and cost-effectiveness of traditional and new partner notification technologies for curable sexually transmitted infections: observational study, systematic reviews and mathematical modelling.

BACKGROUND: Partner notification is essential to the comprehensive case management of sexually transmitted infections. Systematic reviews and mathematical modelling can be used to synthesise information about the effects of new interventions to enhance the outcomes of partner notification. OBJECTIVE: To study the effectiveness and cost-effectiveness of traditional and new partner notification technologies for curable sexually transmitted infections (STIs). DESIGN: Secondary data analysis of clinical audit data; systematic reviews of randomised controlled trials (MEDLINE, EMBASE and Cochrane Central Register of Controlled Trials) published from 1 January 1966 to 31 August 2012 and of studies of health-related quality of life (HRQL) [MEDLINE, EMBASE, ISI Web of Knowledge, NHS Economic Evaluation Database (NHS EED), Database of Abstracts of Reviews of Effects (DARE) and Health Technology Assessment (HTA)] published from 1 January 1980 to 31 December 2011; static models of clinical effectiveness and cost-effectiveness; and dynamic modelling studies to improve parameter estimation and examine effectiveness. SETTING: General population and genitourinary medicine clinic attenders. PARTICIPANTS: Heterosexual women and men. INTERVENTIONS: Traditional partner notification by patient or provider referral, and new partner notification by expedited partner therapy (EPT) or its UK equivalent, accelerated partner therapy (APT). MAIN OUTCOME MEASURES: Population prevalence; index case reinfection; and partners treated per index case. RESULTS: Enhanced partner therapy reduced reinfection in index cases with curable STIs more than simple patient referral [risk ratio (RR) 0.71; 95% confidence interval (CI) 0.56 to 0.89]. There are no randomised trials of APT. The median number of partners treated for chlamydia per index case in UK clinics was 0.60. The number of partners needed to treat to interrupt transmission of chlamydia was lower for casual than for regular partners. In dynamic model simulations, >10% of partners are chlamydia positive with look-back periods of up to 18 months. In the presence of a chlamydia screening programme that reduces population prevalence, treatment of current partners achieves most of the additional reduction in prevalence attributable to partner notification. Dynamic model simulations show that cotesting and treatment for chlamydia and gonorrhoea reduce the prevalence of both STIs. APT has a limited additional effect on prevalence but reduces the rate of index case reinfection. Published quality-adjusted life-year (QALY) weights were of insufficient quality to be used in a cost-effectiveness study of partner notification in this project. Using an intermediate outcome of cost per infection diagnosed, doubling the efficacy of partner notification from 0.4 to 0.8 partners treated per index case was more cost-effective than increasing chlamydia screening coverage. CONCLUSIONS: There is evidence to support the improved clinical effectiveness of EPT in reducing index case reinfection. In a general heterosexual population, partner notification identifies new infected cases but the impact on chlamydia prevalence is limited. Partner notification to notify casual partners might have a greater impact than for regular partners in genitourinary clinic populations. Recommendations for future research are (1) to conduct randomised controlled trials using biological outcomes of the effectiveness of APT and of methods to increase testing for human immunodeficiency virus (HIV) and STIs after APT; (2) collection of HRQL data should be a priority to determine QALYs associated with the sequelae of curable STIs; and (3) standardised parameter sets for curable STIs should be developed for mathematical models of STI transmission that are used for policy-making. FUNDING: The National Institute for Health Research Health Technology Assessment programme

Sex-specific evaluation and redevelopment of the GRACE score in non-ST-segment elevation acute coronary syndromes in populations from the UK and Switzerland: a multinational analysis with external cohort validation.

BACKGROUND The Global Registry of Acute Coronary Events (GRACE) 2.0 score was developed and validated in predominantly male patient populations. We aimed to assess its sex-specific performance in non-ST-segment elevation acute coronary syndromes (NSTE-ACS) and to develop an improved score (GRACE 3.0) that accounts for sex differences in disease characteristics. METHODS We evaluated the GRACE 2.0 score in 420 781 consecutive patients with NSTE-ACS in contemporary nationwide cohorts from the UK and Switzerland. Machine learning models to predict in-hospital mortality were informed by the GRACE variables and developed in sex-disaggregated data from 386 591 patients from England, Wales, and Northern Ireland (split into a training cohort of 309 083 [80·0%] patients and a validation cohort of 77 508 [20·0%] patients). External validation of the GRACE 3.0 score was done in 20 727 patients from Switzerland. FINDINGS Between Jan 1, 2005, and Aug 27, 2020, 400 054 patients with NSTE-ACS in the UK and 20 727 patients with NSTE-ACS in Switzerland were included in the study. Discrimination of in-hospital death by the GRACE 2.0 score was good in male patients (area under the receiver operating characteristic curve [AUC] 0·86, 95% CI 0·86-0·86) and notably lower in female patients (0·82, 95% CI 0·81-0·82; p<0·0001). The GRACE 2.0 score underestimated in-hospital mortality risk in female patients, favouring their incorrect stratification to the low-to-intermediate risk group, for which the score does not indicate early invasive treatment. Accounting for sex differences, GRACE 3.0 showed superior discrimination and good calibration with an AUC of 0·91 (95% CI 0·89-0·92) in male patients and 0·87 (95% CI 0·84-0·89) in female patients in an external cohort validation. GRACE 3·0 led to a clinically relevant reclassification of female patients to the high-risk group. INTERPRETATION The GRACE 2.0 score has limited discriminatory performance and underestimates in-hospital mortality in female patients with NSTE-ACS. The GRACE 3.0 score performs better in men and women and reduces sex inequalities in risk stratification. FUNDING Swiss National Science Foundation, Swiss Heart Foundation, Lindenhof Foundation, Foundation for Cardiovascular Research, and Theodor-Ida-Herzog-Egli Foundation

How nasopharyngeal pneumococcal carriage evolved during and after a PCV13-to-PCV10 vaccination programme switch in Belgium, 2016 to 2018

Background: The current carriage study was set up to reinforce surveillance during/after the PCV13-to-PCVC10 switch in Belgium. Aim: This observational study monitored carriage of Streptococcus pneumoniae (Sp) serotypes, particularly those no longer covered (3, 6A, 19A), as well as Haemophilus influenzae (Hi), because PCV10 contains the non-typeable Hi protein D. Methods: A total of 2,615 nasopharyngeal swabs from children (6-30 months old) attending day care were collected in three periods over 2016-2018. Children's demographic and clinical characteristics and vaccination status were obtained through a questionnaire. Sp and Hi were identified by culture and PCR. Pneumococcal strains were tested for antimicrobial (non-)susceptibility by disc diffusion and serotyped by Quellung-reaction (Quellung-reaction and PCR for serotypes 3, 6A, 19A). Results: The carriage prevalence of Sp (> 75%) remained stable over the successive periods but that of Hi increased (87.4%, 664 Hi-carriers/760 in 2016 vs 93.9%, 895/953 in 2017-2018). The proportion of non-PCV13 vaccine serotypes decreased (94.6%, 438 isolates/463 in 2016 vs 89.7%, 599/668 in 2017-2018) while that of PCV13-non-PCV10 vaccine serotypes (3 + 6A + 19A) increased (0.9%, 4 isolates/463 in 2016 vs 7.8%, 52/668 in 2017-2018), with serotype 19A most frequently identified (87.9%, 58/66 isolates). Non-susceptibility of pneumococci against any of the tested antibiotics was stable over the study period (> 44%). Conclusions: During and after the PCV13-to-PCV10 vaccine switch, the proportion of non-PCV13 serotypes decreased, mainly due to a serotype 19A carriage prevalence increase. These results complement invasive pneumococcal disease surveillance data, providing further basis for pneumococcal vaccination programme policy making

Mathematical models used to inform study design or surveillance systems in infectious diseases : a systematic review

Abstract Background Mathematical models offer the possibility to investigate the infectious disease dynamics over time and may help in informing design of studies. A systematic review was performed in order to determine to what extent mathematical models have been incorporated into the process of planning studies and hence inform study design for infectious diseases transmitted between humans and/or animals. Methods We searched Ovid Medline and two trial registry platforms (Cochrane, WHO) using search terms related to infection, mathematical model, and study design from the earliest dates to October 2016. Eligible publications and registered trials included mathematical models (compartmental, individual-based, or Markov) which were described and used to inform the design of infectious disease studies. We extracted information about the investigated infection, population, model characteristics, and study design. Results We identified 28 unique publications but no registered trials. Focusing on compartmental and individual-based models we found 12 observational/surveillance studies and 11 clinical trials. Infections studied were equally animal and human infectious diseases for the observational/surveillance studies, while all but one between humans for clinical trials. The mathematical models were used to inform, amongst other things, the required sample size (n = 16), the statistical power (n = 9), the frequency at which samples should be taken (n = 6), and from whom (n = 6). Conclusions Despite the fact that mathematical models have been advocated to be used at the planning stage of studies or surveillance systems, they are used scarcely. With only one exception, the publications described theoretical studies, hence, not being utilised in real studies

Clinical, serological and epidemiological features of hepatitis A in León, Nicaragua.

Background and Objectives To monitor and document the endemicity and disease burden of acute hepatitis A in the area of an ongoing vaccine effectiveness study in León, Nicaragua. Methods At community health centres in León, all children, adolescents and young adults presenting with jaundice and/or other clinical signs of hepatitis were offered free serologic screening (hepatitis A, B and C) and blood tests for liver enzymes and bilirubin. Clinical and socioeconomic data were collected with a structured questionnaire. Diagnosis of acute hepatitis A was confirmed by anti-HAV IgM testing. Using logistic regression we compared the characteristics and living conditions of acute hepatitis A cases with those of non-cases. Results Of 557 eligible subjects enrolled between May 2006 and March 2010, 315 (56.6%) were diagnosed with hepatitis A, 80.6% of them ≤10 years and five >18 years of age. No severe cases were encountered. Apart from jaundice (95.6%) and other signs of hepatitis A (fever, pale stool, dark urine, nausea, vomiting, anorexia), two thirds of patients had moderately raised liver enzymes. Cases occurred throughout the year, with highest incidences from August to March. Poor sanitary conditions and crowding were the main risk factors. Conclusions In the study area, hepatitis A is still highly endemic in young and school age children living in low socioeconomic conditions. There are, however, first indications that the endemicity level is shifting from high to high-intermediate

Modelling longitudinal binary outcomes with outcome-dependent observation times : an application to a malaria cohort study

AbstractInspite of the global reduction of 21% in malaria incidence between 2010 and 2015, the disease still threatens many lives of children and pregnant mothers in African countries. A correct assessment and evaluation of the impact of malaria control strategies still remains quintessential in order to eliminate the disease and its burden. Malaria follow-up studies typically involve routine visits at pre-scheduled time points and/or clinical visits whenever individuals experience malaria-like symptoms. In the latter case, infection triggers outcome assessment, thereby leading to outcome-dependent sampling (ODS). Ordinary methods used to analyse such longitudinal data ignore ODS and potentially lead to biased estimates of malaria-specific transmission parameters, hence, inducing an incorrect assessment and evaluation of malaria control strategies. In this paper, we propose novel methodology to handle ODS using a joint model for the longitudinal binary outcome measured at routine visits and the clinical event times. The methodology is applied to malaria parasitaemia data from a cohort of n = 988 Ugandan children aged 0.5–10 years from 3 regions (Walukuba – 300 children, Kihihi – 355 children and Nagongera – 333 children) with varying transmission intensities (entomological inoculation rate equal to 2.8, 32 and 310 infectious bites per unit year, respectively) collected between 2011–2014. The results indicate that malaria parasite prevalence and force of infection (FOI) increase with age in the region of high malaria intensities with FOI highest in age group 5–10 years. For the region of medium intensity, the prevalence slightly increases with age and the FOI for the routine process is highest in age group 5–10 years yet for the clinically observed infections, the FOI gradually decreases with increasing age. For the region with low intensity, both the prevalence and FOI peak at the age of one year after which the former remains constant with age yet the latter suddenly decreases with age for the clinically observed infections. In all study sites, both the prevalence and FOI are highest among previously asymptomatic children and lowest among their symptomatic counterparts. Using a simulation study inspired by the malaria data at hand, the proposed methodology shows to have the smallest bias, especially when consecutive positive malaria parasitaemia presence results within a time period of 35 days were considered to be due to the same infection.</jats:p