Introduction to serocalculator

Overview

The serocalculator R package provides a rapid and computationally simple method for calculating seroconversion rates, as originally published in Simonsen et al. (2009) and Teunis, Eijkeren, et al. (2012), and further developed in deGraaf et al. (2014), Teunis et al. (2016), and Teunis and Eijkeren (2020). In short, longitudinal seroresponses from confirmed cases with a known symptom onset date are assumed to represent the time course of human serum antibodies against a specific pathogen. Therefore, by using these longitudinal antibody dynamics with any cross–sectional sample of the same antibodies in a human population, an incidence estimate can be calculated. Further details are below.

A Proxy for Infection

While the exact time of infection is impossible to measure in an individual, antibody levels measured in a cross–sectional population sample can be translated into an estimate of the frequency with which seroconversions (infections) occur in the sampled population. So the presence of many high antibody concentrations indicates that many people in the population likely experienced infection recently, while mostly low concentrations indicate a low frequency of infections in the sampled population.

In order to interpret the measured cross-sectional antibody concentrations in terms of incidence, we must define the antibody dynamic over time to understand the generalized antibody response at different times since infection. This dynamic must be quantified over time to include an initial increase in serum antibody concentration when seroconversion occurs, followed by a gradual decrease as antibodies wane. In published studies, this information on the time course of the serum antibody response has been obtained from longitudinal follow–up data in cases who had a symptomatic episode following infection. In this case, the onset of symptoms then provides a proxy for the time that infection occurred.

The Seroincidence Estimator

The serocalculator package was designed to calculate the incidence of seroconversion by using the longitudinal seroresponse characteristics. The distribution of serum antibody concentrations in a cross–sectional population sample is calculated as a function of the longitudinal seroresponse and the frequency of seroconversion (or seroincidence). Given the seroresponse, this marginal distribution of antibody concentrations can be fitted to the cross-sectional data and thereby providing a means to estimate the seroincidence.

The Serocalculator App

The serocalculator app is a web based tool that takes the 5 curve parameters (y0, y1, t1, alpha, and r) to draw a single curve on antibody concentration.

Further reading

Methods for estimating seroincidence

• Teunis and Eijkeren (2020)
• Teunis et al. (2016)

Applications

• Aiemjoy et al. (2022)
• Aiemjoy, Rumunu, and Juma John Hassen (2022)
• Monge et al. (2018)
• Kretzschmar, Teunis, and Pebody (2010)
• Simonsen et al. (2007)
• Simonsen et al. (2010)
• Falkenhorst et al. (2012)
• Teunis, Falkenhorst, et al. (2012)
• Demelker et al. (2006)

Quantification of seroresponse

• deGraaf et al. (2014)
• Berbers et al. (2013)
• Versteegh et al. (2005)
• Teunis et al. (2002)

References

Aiemjoy, K., Seidman J. C., Saha S., Munira S. J., Islam Sajib M. S., and Sarkar Sium S. M. al. 2022. “Estimating Typhoid Incidence from Community-Based Serosurveys: A Multicohort Study.” The Lancet Microbe 3 (8): e578–87. https://doi.org/10.1016/S2666-5247(22)00114-8.

Aiemjoy, K., John Rumunu, and Denise Garrett Juma John Hassen Kirsten E. Wiens. 2022. “Seroincidence of Enteric Fever,juba, South Sudan.” Emerging Infectious Diseases 28 (11): 2316–20. https://doi.org/10.3201/eid2811.220239.

Berbers, G. A. M., M. S. E. van de Wetering, P. G. M. van Gageldonk, J. F. P. Schellekens, F. G. A. Versteegh, and P. F. M. Teunis. 2013. “A Novel Method for Evaluating Natural and Vaccine Induced Serological Responses to Bordetella Pertussis Antigens.” Vaccine 31 (36): 3732–38. https://doi.org/10.1016/j.vaccine.2013.05.073.

deGraaf, W. F., M. E. E. Kretzschmar, P. F. M. Teunis, and O. Diekmann. 2014. “A Two-Phase Within-Host Model for Immune Response and Its Application to Serological Profiles of Pertussis.” Epidemics 9 (December): 1–7. https://doi.org/10.1016/j.epidem.2014.08.002.

Demelker, H, F Versteegh, J Schellekens, P Teunis, and M Kretzschmar. 2006. “The Incidence of Bordetella Pertussis Infections Estimated in the Population from a Combination of Serological Surveys.” Journal of Infection 53 (2): 106–13. https://doi.org/10.1016/j.jinf.2005.10.020.

Falkenhorst, Gerhard, Jacob Simonsen, Tina H Ceper, Wilfrid van Pelt, Henriette de Valk, Malgorzata Sadkowska-Todys, Lavinia Zota, et al. 2012. “Serological Cross-Sectional Studies on Salmonella Incidence in Eight European Countries: No Correlation with Incidence of Reported Cases.” BMC Public Health 12 (1). https://doi.org/10.1186/1471-2458-12-523.

Kretzschmar, Mirjam, Peter F. M. Teunis, and Richard G. Pebody. 2010. “Incidence and Reproduction Numbers of Pertussis: Estimates from Serological and Social Contact Data in Five European Countries.” Edited by Megan Murray. PLoS Medicine 7 (6): e1000291. https://doi.org/10.1371/journal.pmed.1000291.

Monge, Susana, Peter Teunis, Ingrid Friesema, Eelco Franz, Wim Ang, Wilfrid van Pelt, and Lapo Mughini-Gras. 2018. “Immune Response-Eliciting Exposure to Campylobacter Vastly Exceeds the Incidence of Clinically Overt Campylobacteriosis but Is Associated with Similar Risk Factors: A Nationwide Serosurvey in the Netherlands.” Journal of Infection 77 (3): 171–77. https://doi.org/10.1016/j.jinf.2018.04.016.

Simonsen, J., K. Mølbak, G. Falkenhorst, K. A. Krogfelt, A. Linneberg, and P. F. M. Teunis. 2009. “Estimation of Incidences of Infectious Diseases Based on Antibody Measurements.” Statistics in Medicine 28 (14): 1882–95. https://doi.org/10.1002/sim.3592.

Simonsen, J., M. A. Strid, K. Mølbak, K. A. Krogfelt, A. Linneberg, and P. Teunis. 2007. “Sero-Epidemiology as a Tool to Study the Incidence of Salmonella Infections in Humans.” Epidemiology and Infection 136 (7): 895–902. https://doi.org/10.1017/s0950268807009314.

Simonsen, J., P. Teunis, W. van Pelt, Y. Van Duynhoven, K. A. Krogfelt, M. Sadkowska-Todys, and K. Mølbak. 2010. “Usefulness of Seroconversion Rates for Comparing Infection Pressures Between Countries.” Epidemiology and Infection 139 (4): 636–43. https://doi.org/10.1017/s0950268810000750.

Teunis, P. F. M., and J. C. H. van Eijkeren. 2020. “Estimation of Seroconversion Rates for Infectious Diseases: Effects of Age and Noise.” Statistics in Medicine 39 (21): 2799–2814. https://doi.org/10.1002/sim.8578.

Teunis, P. F. M., J. C. H. van Eijkeren, W. F. de Graaf, A. Bonačić Marinović, and M. E. E. Kretzschmar. 2016. “Linking the Seroresponse to Infection to Within-Host Heterogeneity in Antibody Production.” Epidemics 16 (September): 33–39. https://doi.org/10.1016/j.epidem.2016.04.001.

Teunis, P. F. M., JCH van Eijkeren, CW Ang, YTHP van Duynhoven, JB Simonsen, MA Strid, and W van Pelt. 2012. “Biomarker Dynamics: Estimating Infection Rates from Serological Data.” Statistics in Medicine 31 (20): 2240–48. https://doi.org/10.1002/sim.5322.

Teunis, P. F. M., G. Falkenhorst, C. W. Ang, M. A. Strid, H. de Valk, M. Sadkowksa-Todys, L. Zota, et al. 2012. “Campylobacterseroconversion Rates in Selected Countries in the European Union.” Epidemiology and Infection 141 (10): 2051–57. https://doi.org/10.1017/s0950268812002774.

Teunis, P. F. M., O. G. van der Heijden, H. E. de Melker, J. F. P. Schellekens, F. G. A. Versteegh, and M. E. E. Kretzshmar. 2002. “Kinetics of the IgG Antibody Response to Pertussis Toxin After Infection with b. Pertussis.” Epidemiology and Infection 129 (3): 479–89. https://doi.org/10.1017/s0950268802007896.

Versteegh, F. G. A., P. L. J. M. Mertens, H. E. de Melker, J. J. Roord, J. F. P. Schellekens, and P. F. M. Teunis. 2005. “Age-Specific Long-Term Course of IgG Antibodies to Pertussis Toxin After Symptomatic Infection with Bordetella Pertussis.” Epidemiology and Infection 133 (4): 737–48. https://doi.org/10.1017/s0950268805003833.