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Althaus, C.

Publications and source records attributed to Althaus, C..

2 recordsLinked to original sources
bioRxiv2018

Gini coefficients for measuring the distribution of sexually transmitted infections among individuals with different levels of sexual activity

ObjectivesGini coefficients have been used to describe the distribution of Chlamydia trachomatis (CT) infections among individuals with different levels of sexual activity. The objectives of this study were to investigate Gini coefficients for different sexually transmitted infections (STIs), and to determine how STI control interventions might affect the Gini coefficient over time.\n\nMethodsWe used population-based data for sexually experienced women from two British National Surveys of Sexual Attitudes and Lifestyles (Natsal-2: 1999-2001; Natsal-3: 2010-2012) to calculate Gini coefficients for CT, Mycoplasma genitalium (MG), and human papillomavirus (HPV) types 6, 11, 16 and 18. We applied bootstrap methods to assess uncertainty and to compare Gini coefficients for different STIs. We then used a mathematical model of STI transmission to study how control interventions affect Gini coefficients.\n\nResultsGini coefficients for CT and MG were 0.33 (95% confidence interval (CI): 0.18-0.49) and 0.16 (95% CI: 0.02-0.36), respectively. The relatively small coefficient for MG suggests a longer infectious duration compared with CT. The coefficients for HPV types 6, 11, 16 and 18 ranged from 0.15-0.38. During the decade between Natsal-2 and Natsal-3, the Gini coefficient for CT did not change. The transmission model shows that higher STI treatment rates are expected to reduce prevalence and increase the Gini coefficient of STIs. In contrast, increased condom use reduces STI prevalence but does not affect the Gini coefficient.\n\nConclusionsGini coefficients for STIs can help us to understand the distribution of STIs in the population, according to level of sexual activity, and could be used to inform STI prevention and treatment strategies.\n\nKey messagesO_LIThe Gini coefficient can be used to describe the distribution of STIs in a population, according to different levels of sexual activity.\nC_LIO_LIGini coefficients for Chlamydia trachomatis (CT) and human papillomavirus (HPV) type 18 appear to be higher than for Mycoplasma genitalium and HPV 6, 11 and 16.\nC_LIO_LIMathematical modelling suggests that CT screening interventions should reduce prevalence and increase the Gini coefficient, whilst condom use reduces prevalence without affecting the Gini coefficient.\nC_LIO_LIChanges in Gini coefficients over time could be used to assess the impact of STI prevention and treatment strategies.\nC_LI

epidemiology↗
bioRxiv2018

Transmission of and susceptibility to seasonal influenza in Switzerland from 2003-2015

Understanding the seasonal patterns of influenza transmission is critical to help plan public health measures for the management and control of epidemics. Mathematical models of infectious disease transmission have been widely used to quantify the transmissibility of and susceptibility to past influenza seasons in many countries. The objective of this study was to obtain a detailed picture of the transmission dynamics of seasonal influenza in Switzerland from 2003-2015. To this end, we developed a compartmental influenza transmission model taking into account social mixing between different age groups and seasonal forcing. We applied a Bayesian approach using Markov chain Monte Carlo (MCMC) methods to fit the model to the reported incidence of influenza-like-illness (ILI) and virological data from Sentinella, the Swiss Sentinel Surveillance Network. The maximal basic reproduction number, R0, ranged from 1.46 to 1.81 (median). Median estimates of susceptibility to influenza ranged from 29% to 98% for different age groups, and typically decreased with age. We also found a decline in ascertainability of influenza cases with age. Our study illustrates how influenza surveillance data from Switzerland can be integrated into a Bayesian modeling framework in order to assess age-specific transmission of and susceptibility to influenza.

epidemiology↗