An individual-based network model to evaluate interventions for controlling pneumococcal transmission

Lessons from a decade of individual-based models for infectious disease transmission: a systematic review (2006-2015)

Background

Individual-based models (IBMs) are useful to simulate events subject to stochasticity and/or heterogeneity, and have become well established to model the potential (re)emergence of pathogens (e.g., pandemic influenza, bioterrorism). Individual heterogeneity at the host and pathogen level is increasingly documented to influence transmission of endemic diseases and it is well understood that the final stages of elimination strategies for vaccine-preventable childhood diseases (e.g., polio, measles) are subject to stochasticity. Even so it appears IBMs for both these phenomena are not well established. We review a decade of IBM publications aiming to obtain insights in their advantages, pitfalls and rationale for use and to make recommendations facilitating knowledge transfer within and across disciplines.

Methods

We systematically identified publications in Web of Science and PubMed from 2006-2015 based on title/abstract/keywords screening (and full-text if necessary) to retrieve topics, modeling purposes and general specifications. We extracted detailed modeling features from papers on established vaccine-preventable childhood diseases based on full-text screening.

Results

We identified 698 papers, which applied an IBM for infectious disease transmission, and listed these in a reference database, describing their general characteristics. The diversity of disease-topics and overall publication frequency have increased over time (38 to 115 annual publications from 2006 to 2015). The inclusion of intervention strategies (8 to 52) and economic consequences (1 to 20) are increasing, to the detriment of purely theoretical explorations. Unfortunately, terminology used to describe IBMs is inconsistent and ambiguous. We retrieved 24 studies on a vaccine-preventable childhood disease (covering 7 different diseases), with publication frequency increasing from the first such study published in 2008. IBMs have been useful to explore heterogeneous between- and within-host interactions, but combined applications are still sparse. The amount of missing information on model characteristics and study design is remarkable.

Conclusions

IBMs are suited to combine heterogeneous within- and between-host interactions, which offers many opportunities, especially to analyze targeted interventions for endemic infections. We advocate the exchange of (open-source) platforms and stress the need for consistent “branding”. Using (existing) conventions and reporting protocols would stimulate cross-fertilization between research groups and fields, and ultimately policy making in decades to come.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-017-2699-8) contains supplementary material, which is available to authorized users.

Long-term effects of penicillin resistance and fitness cost on pneumococcal transmission dynamics in a developed setting

BACKGROUND

The increasing prevalence of penicillin non-susceptible pneumococci (PNSP) throughout the world threatens successful treatment of infections caused by this important bacterial pathogen. The rate at which PNSP clones spread in the community is thought to mainly be determined by two key determinants; the volume of penicillin use and the magnitude of the fitness cost in the absence of treatment. The aim of the study was to determine the impacts of penicillin consumption and fitness cost on pneumococcal transmission dynamics in a developed country setting.

METHODS

An individual-based network model based on real-life demographic data was constructed and applied in a developed country setting (Sweden). A population structure with transmission of carriage taking place within relevant mixing groups, i.e. families, day care groups, school classes, and other close contacts, was considered to properly assess the transmission dynamics for susceptible and PNSP clones. Several scenarios were simulated and model outcomes were statistically analysed.

RESULTS

Model simulations predicted that with an outpatient penicillin use corresponding to the sales in Sweden 2010 (118 recipes per 1,000 inhabitants per year), the magnitude of a fitness cost for resistance must be at least 5% to offset the advantage of penicillin resistance. Moreover, even if there is a fitness cost associated with penicillin resistance, a considerable reduction of penicillin usage appears to be required to significantly decrease the incidence of PNSP in a community.

CONCLUSION

The frequency of PNSP clones is hard to reverse by simply reducing the penicillin consumption even if there is a biological cost associated with resistance. However, because penicillin usage does promote further spread of PNSP clones, it is important to keep down penicillin consumption considering future resistance problems.

Choosing between 7-, 10- and 13-valent pneumococcal conjugate vaccines in childhood: a review of economic evaluations (2006-2014)

BACKGROUND

Seven-valent pneumococcal conjugate vaccines (PCV7) have been used in children for more than a decade. Given the observed increase in disease caused by pneumococcal serotypes not covered by PCV7, an increasing number of countries are switching from 7-valent to 10- and 13-valent PCVs ("PCV10" and "PCV13"). Economic evaluations are important tools to inform decisions and price negotiations to make such a switch.

OBJECTIVE

This review aims to provide a critical assessment of economic evaluations involving PCV10 or PCV13, published since 2006.

METHODS

We searched Scopus, ISI Web of Science (SCI and SSCI) and Pubmed to retrieve, select and review relevant studies, which were archived between 1st January 2006 and 31st January 2014. The review protocol involved standard extraction of assumptions, methods, results and sponsorships from the original studies.

RESULTS

Sixty-three economic evaluations on PCVs published since January 2006 were identified. About half of these evaluated PCV10 and/or PCV13, the subject of this review. At current prices, both PCV13 and PCV10 were likely judged preferable to PCV7. However, the combined uncertainty related to price differences, burden of disease, vaccine effectiveness, herd and serotype replacement effects determine the preference base for either PCV10 or PCV13. The pivotal assumptions and results of these analyses also depended on which manufacturer sponsored the study.

CONCLUSION

A more thorough exploration of uncertainty should be made in future analyses on this subject, as we lack understanding to adequately model herd and serotype replacement effects to reliably predict the population impact of PCVs. The introduction of further improved PCVs in an environment of evolving antibiotic resistance and under the continuing influence of previous PCVs implies that the complexity and data requirements for relevant analyses will further increase. Decision makers using these analyses should not just rely on an analysis from a single manufacturer.

Risk factors for pneumococcal carriage in day care centers: a retrospective study during a 10-year period

In this retrospective epidemiologic study, we present pneumococcal carriage data from 109 Swedish day care centers over a period of 10 years. Aspects of season, age, personnel and group size were studied. We found a significant seasonal variation in pneumococcal carriage. Group size was a significant risk factor for pneumococcal carriage. Pneumococcal carriage was 4.5 % in personnel.

Contribution of mathematical modeling to the fight against bacterial antibiotic resistance

PURPOSE OF REVIEW

Modeling of antibiotic resistance in pathogenic bacteria responsible for human disease has developed considerably over the last decade. Herein, we summarize the main published studies to illustrate the contribution of models for understanding both within-host and population-based phenomena. We then suggest possible topics for future studies.

RECENT FINDINGS

Model building of bacterial resistance has involved epidemiologists, biologists and modelers with two different objectives. First, modeling has helped largely in identifying and understanding the factors and biological phenomena responsible for the emergence and spread of resistant strains. Second, these models have become important decision support tools for medicine and public health.

SUMMARY

Major improvements of models in the coming years should take into account specific pathogen characteristics (resistance mechanisms, multiple colonization phenomena, cooperation and competition among species) and better description of the contacts associated with transmission risk within populations.

Modelling the effects of population structure on childhood disease: the case of varicella

Realistic, individual-based models based on detailed census data are increasingly used to study disease transmission. Whether the rich structure of such models improves predictions is debated. This is studied here for the spread of varicella, a childhood disease, in a realistic population of children where infection occurs in the household, at school, or in the community at large. A methodology is first presented for simulating households with births and aging. Transmission probabilities were fitted for schools and community, which reproduced the overall cumulative incidence of varicella over the age range of 0-11 years old.Moreover, the individual-based model structure allowed us to reproduce several observed features of VZV epidemiology which were not included as hypotheses in the model: the age at varicella in first-born children was older than in other children, in accordance with observation; the same was true for children residing in rural areas. Model predicted incidence was comparable to observed incidence over time. These results show that models based on detailed census data on a small scale provide valid small scale prediction. By simulating several scenarios, we evaluate how varicella epidemiology is shaped by policies, such as age at first school enrolment, and school eviction. This supports the use of such models for investigating outcomes of public health measures.

Probabilistic network modelling of the impact of penicillin consumption on spread of pneumococci

The worldwide increase of resistant S. pneumoniae is a growing clinical problem. In several countries, a more restrictive use of penicillin has been promoted in hope of slowing the rates of resistant pneumococci. However, the consequences of such an action on pneumococcal population dynamics are not fully understood. Thus, a network model was constructed to assess the impacts of penicillin consumption and between-strain competition on the spread of penicillin non-susceptible pneumococci. Model simulations suggest that the age distribution for carriage of penicillin non-susceptible pneumococci, in contrast to susceptible pneumococci, is affected by penicillin consumption. Furthermore, it appears extremely difficult to reduce the incidence of penicillin non-susceptible pneumococci by simply controlling penicillin consumption, assuming that reduced penicillin susceptibility does not confer a fitness cost for the organism. A more judicious use of penicillin together with control measures are in that case required to manage penicillin resistance in pneumococci.