Åke Svensson

Risk factors for domestic sporadic campylobacteriosis among young children in Sweden

A case-control study was conducted in Sweden to study risk factors for domestically acquired Campylobacter jejuni/coli infections among children aged less than 6 y. A total of 126 cases, reported to the national surveillance system were recruited over 1 y. Controls, selected from the population register, were matched to the cases by age, gender, place of residence and time of infection of the case. Information was gathered by posted questionnaires. Two separate conditional regression models were developed including and excluding ‘protective’ factors. Two of the factors significantly associated with Campylobacter infection were water-related: having a well in the household (OR=2.6) and drinking water from a lake/river (OR=7.4; 6.0). Other exposures associated with increased risk were: having a dog (OR=8.4; 3.8) and eating grilled meat (OR=5.5; 2.1). Drinking unpasteurized milk was borderline significant in 1 model (OR=3.7). Eating sausage was protective (OR=0.05). Eating chicken was not a significant risk. Exposures such as eating grilled meat and drinking water from a lake or a river were more common in the warm months, a factor that may partly explain the observed seasonality. The authors suggest that differences between risk factors across studies may reflect geographical and age-specific differences in the sources of infection.

Association between environmental risk factors and campylobacter infections in Sweden.

Campylobacter sp. is the most common cause of acute bacterial gastroenteritis in Sweden and the incidence has been increasing. Case-control studies to identify risk factors have been conducted in several countries, but much remains unexplained. The geographical distribution of campylobacter infections varies substantially, and many environmental factors may influence the observed pattern. Geographical Information Systems (GIS) offer an opportunity to use routinely available surveillance data to explore associations between potential environmental risk factors showing a geographical pattern and disease incidence, complementing traditional approaches for investigating risk factors for disease. We investigated associations between campylobacter incidence and environmental factors related to water and livestock in Sweden. Poisson regression was used to estimate the strength of the associations. Positive associations were found between campylobacter incidence and average water-pipe length per person, ruminant density, and a negative association with the percentage of the population receiving water from a public water supply. This indicates that drinking water and contamination from livestock may be important factors in explaining sporadic human campylobacteriosis in Sweden, and that contamination occurring in the water distribution system might be more important than previously considered.

Cause of death in individuals with chronic HBV and/or HCV infection, a nationwide community‐based register study

Summary.  Studies on chronic viral hepatitis and mortality have often been made on selected populations or in high‐endemic countries. The aim of this study was to investigate the causes of death and the mortality rates in the nationwide cohorts of people chronically infected with hepatitis B virus (HBV) and/or hepatitis C virus (HCV) in Sweden, a low‐endemic country. All notifications on chronic HBV infection and HCV infection 1990–2003 were linked to the Cause of Death Register. A total of 9517 people with chronic HBV infection, 34 235 people with HCV infection and 1601 with chronic HBV–HCV co‐infection were included, and the mean observation times were 6.4, 6.3 and 7.9 years, respectively. The mortality in the cohorts was compared with age‐ and gender‐specific mortality in the general population and standardized mortality ratios (SMR) were calculated. All‐cause mortality was significantly increased, SMR 2.3 (HBV), 5.8 (HCV) and 8.5 (HBV–HCV), with a great excess liver‐related mortality in all cohorts, SMR 21.7, 35.5 and 46.2, respectively. In HCV and HBV–HCV infected there was an increased mortality due to drug‐related psychiatric diagnoses (SMR: 20.7 and 27.6) and external causes (SMR: 12.4 and 11.4), predominantly at younger age. To conclude, this study demonstrated an increased all‐cause mortality, with a great excess mortality from liver disease, in all cohorts. In people with HCV infection the highest excess mortality in younger ages was from drug‐related and external reasons.

Sources of sporadic Yersinia enterocolitica infection in children in Sweden, 2004: a case-control study

Young children account for a large proportion of reported Yersinia enterocolitica infections in Sweden with a high incidence compared with other gastrointestinal infections, such as salmonellosis and campylobacteriosis. A case-control study was conducted to investigate selected risk factors for domestic sporadic yersiniosis in children aged 0-6 years in Sweden. In total, 117 cases and 339 controls were included in the study. To minimize exclusion of observations due to missing data a multiple non-parametric imputation technique was used. The following risk factors were identified in the multivariate analysis: eating food prepared from raw pork products (OR 3.0, 95% CI 1.8-5.1) or treated sausage (OR 1.9, 95% CI 1.1-3.3), use of a babys dummy (OR 1.9, 95% CI 1.1-3.2) and contact with domestic animals (OR 2.0, 95% CI 1.2-3.4). We believe that the importance of Y. enterocolitica infection in children has been neglected and that results from this study can be used to develop preventive recommendations.

A Proposed Method to Adjust for Selection Bias in Cohort Studies

Selection bias is a concern in cohort studies in which selection into the cohort is related to the studied outcome. An example is chronic infection with hepatitis C virus, where the initial infection may be asymptomatic for decades. This problem leads to selection of more severely ill individuals into registers of such infections. Cohort studies often adjust for this bias by introducing a time window between entry into the cohort and entry into the study. This paper describes and assesses a novel method to improve adjustment for this type of selection bias. The size of the time window is decided by calculating a standardized incidence ratio as a continuous function of the size of the time window. The resulting graph is used to decide on an appropriate window size. The method is evaluated by using the Swedish register of hepatitis C virus infections for 1990-2006. The complications studied were non-Hodgkin lymphoma and liver cancer. Selection bias differed for the studied outcomes, and a time window of a minimum of 2 months and 12 months, respectively, was judged to be appropriate. The novel method may have advantages compared with an interval-based method, especially in cohort studies with small numbers of events.

Analyzing effects of vaccines

A population with (individually) varying susceptibilities to infection and a vaccine with (individually) varying protective effect are considered. A simple stochastic model is used to illustrate different effects of the vaccine on the spread of the infection. The behavior of different estimators of the vaccine efficacy using data from a clinical trial and the relation between vaccine efficacy and the effectiveness of a vaccination program are discussed.

The underreporting of hepatocellular carcinoma to the Cancer Register and a log-linear model to estimate a more correct incidence

The Cancer Register (CR) in Sweden has reported that the incidence of primary liver cancer (PLC) has slowly declined over the last decades. Even though all cancers, irrespective of diagnostic method, should be reported to the CR, the PLC incidence may not reflect the true rate. Improved diagnostic tools have enabled diagnosis of hepatocellular carcinoma based on noninvasive methods without histological verification, possibly associated with missed cancer reports or misclassification in the CR. Our objective was to study the completeness and assess the underreporting of PLC to the CR and to produce a more accurate estimate based on three registers. The CR, the Cause of Death Register, and the Patient Register were investigated. Differences and overlap were examined, the incidence was estimated by merging data from the registers, and the number reported to none of the registers was estimated using a log‐linear capture‐recapture model. The results show that 98% of the PLCs reported to the CR were histologically verified; 80% were hepatocellular carcinoma and 20% were intrahepatic cholangiocarcinoma. Unspecified liver cancer decreased over time and constituted <10% of all reported liver cancers. The CR may underestimate the liver cancer incidence by 37%‐45%, primarily due to missed cancer reports. The estimated annual number of liver cancers increased over time, but the standardized incidence was stable around 11 per 100,000. Hepatitis C‐associated liver cancer increased and constituted 20% in 2010. Conclusion: There was an underreporting of PLC diagnosed by noninvasive methods; the incidence was considerably higher than estimated by the CR, with a stable incidence over time; reporting needs to improve and combining registers is recommended when studying incidence. (Hepatology 2017;65:885‐892).

Networks, Epidemics and Vaccination through Contact Tracing

We consider a (social) network whose structure can be represented by a simple random graph having a pre-specified degree distribution. A Markovian susceptible-infectious-removed (SIR) epidemic model is defined on such a social graph. We then consider two real-time vaccination models for contact tracing during the early stages of an epidemic outbreak. The first model considers vaccination of each friend of an infectious individual (once identified) independently with probability p. The second model is related to the first model but also sets a bound on the maximum number an infectious individual can infect before being identified. Expressions are derived for the influence on the reproduction number of these vaccination models. We give some numerical examples and simulation results based on the Poisson and heavy-tail degree distributions where it is shown that the second vaccination model has a bigger advantage compared to the first model for the heavy-tail degree distribution.

Household Epidemics: Modelling Effects of Early Stage Vaccination

A Markovian susceptible --> infectious --> removed (SIR) epidemic model is considered in a community partitioned into households. A vaccination strategy, which is implemented during the early stages of the disease following the detection of infected individuals is proposed. In this strategy, the detection occurs while an individual is infectious and other susceptible household members are vaccinated without further delay. Expressions are derived for the influence on the reproduction numbers of this vaccination strategy for equal and unequal household sizes. We fit previously estimated parameters from influenza and use household distributions for Sweden and Tanzania census data. The results show that the reproduction number is much higher in Tanzania (6 compared with 2) due to larger households, and that infected individuals have to be detected (and household members vaccinated) after on average 5 days in Sweden and after 3.3 days in Tanzania, a much smaller difference.

A multi-type branching model with varying environment for bacterial dynamics with postantibiotic effect

A multi-type branching process with varying environment was used to construct a pharmacokinetic/pharmacodynamic (PK/PD) model that captures the postantibiotic effect (PAE) seen in bacterial populations after exposure of antibiotics. This phenomenon of continued inhibition of bacterial growth even after removal of the antibiotic from the growth medium is of high relevance in the context of optimizing dosing regimens. The clinical implication of long PAEs lies in the interesting possibility of increasing the intervals between drug administrations. The model structure is generalizable to most types of antibiotics and is useful both as a theoretical framework for understanding the time properties of PAE and to explore optimal antibiotic dosing regimens. Data from an in vitro study with Escherichia coli exposed to different dosing regimens of cefotaxime were used to evaluate the model.