Marika Hjertqvist

Why is tick-borne encephalitis increasing? A review of the key factors causing the increasing incidence of human TBE in Sweden

The highest annual incidence of human tick-borne encephalitis (TBE) in Sweden ever recorded by the Swedish Institute for Communicable Disease Control (SMI) occurred last year, 2011. The number of TBE cases recorded during 2012 up to 6th August 2012 indicates that the incidence for 2012 could exceed that of 2011. In this review of the ecology and epidemiology of TBE in Sweden our main aim is to analyse the possible reasons behind the gradually increasing incidence of human TBE during the last 20 years. The main TBE virus (TBEV) vector to humans in Sweden is the nymphal stage of the common tick Ixodes ricinus. The main mode of transmission and maintenance of TBEV in the tick population is considered to be when infective nymphs co-feed with uninfected but infectible larvae on rodents. In most locations the roe deer, Capreolus capreolus is the main host for the reproducing adult I. ricinu s ticks. The high number of roe deer for more than three decades has resulted in a very large tick population. Deer numbers have, however, gradually declined from the early 1990s to the present. This decline in roe deer numbers most likely made the populations of small rodents, which are reservoir-competent for TBEV, gradually more important as hosts for the immature ticks. Consequently, the abundance of TBEV-infected ticks has increased. Two harsh winters in 2009–2011 caused a more abrupt decline in roe deer numbers. This likely forced a substantial proportion of the “host-seeking” ticks to feed on bank voles (Myodes glareolus), which at that time suddenly had become very numerous, rather than on roe deer. Thus, the bank vole population peak in 2010 most likely caused many tick larvae to feed on reservoir-competent rodents. This presumably resulted in increased transmission of TBEV among ticks and therefore increased the density of infected ticks the following year. The unusually warm, humid weather and the prolonged vegetation period in 2011 permitted nymphs and adult ticks to quest for hosts nearly all days of that year. These weather conditions stimulated many people to spend time outdoors in areas where they were at risk of being attacked by infective nymphs. This resulted in at least 284 human cases of overt TBE. The tick season of 2012 also started early with an exceptionally warm March. The abundance of TBEV-infective “hungry” ticks was presumably still relatively high. Precipitation during June and July was rich and will lead to a “good mushroom season”. These factors together are likely to result in a TBE incidence of 2012 similar to or higher than that of 2011.

Mortality rate patterns for hemorrhagic fever with renal syndrome caused by puumala virus.

To investigate nephropathia epidemica in Sweden during 1997-2007, we determined case-fatality rates for 5,282 patients with this disease. Overall, 0.4% died of acute nephropathia epidemica ≤3 months after diagnosis. Case-fatality rates increased with age. Only women showed an increased case-fatality rate during the first year after diagnosis.

Predicting High Risk for Human Hantavirus Infections, Sweden

An increased risk for hemorrhagic fever with renal syndrome caused by Puumala hantavirus was forecast for Sweden in 2007. The forecast was based on a predicted increase in the number of Myodes glareolus rodents (reservoir hosts). Despite raised awareness and preparedness, the number of human cases during July 2007–June 2008 was 1,483, a new high.

Combining information from surveys of several species to estimate the probability of freedom from Echinococcus multilocularis in Sweden, Finland and mainland Norway

BackgroundThe fox tapeworm Echinococcus multilocularis has foxes and other canids as definitive host and rodents as intermediate hosts. However, most mammals can be accidental intermediate hosts and the larval stage may cause serious disease in humans. The parasite has never been detected in Sweden, Finland and mainland Norway. All three countries require currently an anthelminthic treatment for dogs and cats prior to entry in order to prevent introduction of the parasite. Documentation of freedom from E. multilocularis is necessary for justification of the present import requirements.MethodsThe probability that Sweden, Finland and mainland Norway were free from E. multilocularis and the sensitivity of the surveillance systems were estimated using scenario trees. Surveillance data from five animal species were included in the study: red fox (Vulpes vulpes), raccoon dog (Nyctereutes procyonoides), domestic pig, wild boar (Sus scrofa) and voles and lemmings (Arvicolinae).ResultsThe cumulative probability of freedom from EM in December 2009 was high in all three countries, 0.98 (95% CI 0.96-0.99) in Finland and 0.99 (0.97-0.995) in Sweden and 0.98 (0.95-0.99) in Norway.ConclusionsResults from the model confirm that there is a high probability that in 2009 the countries were free from E. multilocularis. The sensitivity analyses showed that the choice of the design prevalences in different infected populations was influential. Therefore more knowledge on expected prevalences for E. multilocularis in infected populations of different species is desirable to reduce residual uncertainty of the results.

Vector-borne disease intelligence: strategies to deal with disease burden and threats

Owing to the complex nature of vector-borne diseases (VBDs), whereby monitoring of human case patients does not suffice, public health authorities experience challenges in surveillance and control of VBDs. Knowledge on the presence and distribution of vectors and the pathogens that they transmit is vital to the risk assessment process to permit effective early warning, surveillance, and control of VBDs. Upon accepting this reality, public health authorities face an ever-increasing range of possible surveillance targets and an associated prioritization process. Here, we propose a comprehensive approach that integrates three surveillance strategies: population-based surveillance, disease-based surveillance, and context-based surveillance for EU member states to tailor the best surveillance strategy for control of VBDs in their geographic region. By classifying the surveillance structure into five different contexts, we hope to provide guidance in optimizing surveillance efforts. Contextual surveillance strategies for VBDs entail combining organization and data collection approaches that result in disease intelligence rather than a preset static structure.

Epidemiology and ecology of tularemia in Sweden, 1984-2012.

Geographic distribution of cases was correlated with the locations of lakes and rivers.

The importance of bank vole density and rainy winters in predicting nephropathia epidemica incidence in Northern Sweden.

Pathogenic hantaviruses (family Bunyaviridae, genus Hantavirus) are rodent-borne viruses causing hemorrhagic fever with renal syndrome (HFRS) in Eurasia. In Europe, there are more than 10,000 yearly cases of nephropathia epidemica (NE), a mild form of HFRS caused by Puumala virus (PUUV). The common and widely distributed bank vole (Myodes glareolus) is the host of PUUV. In this study, we aim to explain and predict NE incidence in boreal Sweden using bank vole densities. We tested whether the number of rainy days in winter contributed to variation in NE incidence. We forecast NE incidence in July 2013–June 2014 using projected autumn vole density, and then considering two climatic scenarios: 1) rain-free winter and 2) winter with many rainy days. Autumn vole density was a strong explanatory variable of NE incidence in boreal Sweden in 1990–2012 (R2 = 79%, p<0.001). Adding the number of rainy winter days improved the model (R2 = 84%, p<0.05). We report for the first time that risk of NE is higher in winters with many rainy days. Rain on snow and ground icing may block vole access to subnivean space. Seeking refuge from adverse conditions and shelter from predators, voles may infest buildings, increasing infection risk. In a rainy winter scenario, we predicted 812 NE cases in boreal Sweden, triple the number of cases predicted in a rain-free winter in 2013/2014. Our model enables identification of high risk years when preparedness in the public health sector is crucial, as a rainy winter would accentuate risk.

Shaping zoonosis risk: landscape ecology vs. landscape attractiveness for people, the case of tick-borne encephalitis in Sweden

BackgroundIn this paper, the hazard and exposure concepts from risk assessment are applied in an innovative approach to understand zoonotic disease risk. Hazard is here related to the landscape ecology determining where the hosts, vectors and pathogens are and, exposure is defined as the attractiveness and accessibility to hazardous areas. Tick-borne encephalitis in Sweden was used as a case study.MethodsThree boosted regression tree models are compared: a hazard model, an exposure model and a global model which combines the two approaches.ResultsThe global model offers the best predictive power and the most accurate modelling. The highest probabilities were found in easy-to-reach places with high landscape diversity, holiday houses, waterbodies and, well-connected forests of oak, birch or pine, with open-area in their ecotones, a complex shape, numerous clear-cuts and, a variation in tree height.ConclusionWhile conditions for access and use of hazardous areas are quite specific to Scandinavia, this study offers promising perspectives to improve our understanding of the distribution of zoonotic and vector-borne diseases in diverse contexts.

Risk factors and potential preventive measures for nephropatia epidemica in Sweden 2011–2012: a case–control study

Introduction Nephropatia epidemica (NE), a relatively mild form of hemorrhagic fever with renal syndrome caused by the Puumala virus (PUUV), is endemic in northern Sweden. We aim to study the risk factors associated with NE in this region. Methods We conducted a matched case–control study between June 2011 and July 2012. We compared confirmed NE cases with randomly selected controls, matched by age, sex, and place of infection or residence. We analyzed the association between NE and several occupational, environmental, and behavioral exposures using conditional logistic regression. Results We included in the final analysis 114 cases and 300 controls, forming 246 case–control pairs. Living in a house with an open space beneath, making house repairs, living less than 50 m from the forest, seeing rodents, and smoking were significantly associated with NE. Conclusion Our results could orient public health policies targeting these risk factors and subsequently reduce the NE burden in the region.

Landscape and regional environmental analysis of the spatial distribution of hantavirus human cases in Europe

Background: In Europe, the most prevalent hantavirus, Puumala virus, is transmitted by bank voles and causes nephropathia epidemica in human. The European spatial distribution of nephropathia epidemica is investigated here for the first time with a rich set of environmental variables. Methods: The influence of variables at the landscape and regional level is studied through multilevel logistic regression, and further information on their effects across the different European ecoregions is obtained by comparing an overall niche model (boosted regression trees) with regressions by ecoregion. Results: The presence of nephropathia epidemica is likely in populated regions with well-connected forests, more intense vegetation activity, low soil water content, mild summers, and cold winters. In these regions, landscapes with a higher proportion of built-up areas in forest ecotones and lower minimum temperature in winter are expected to be more at risk. Climate and forest connectivity have a stronger effect at the regional level. If variables are staying at their current values, the models predict that nephropathia epidemica may know intensification but should not spread (although southern Sweden, the Norwegian coast, and the Netherlands should be kept under watch). Conclusion: Models indicate that large-scale modeling can lead to a very high predictive power. At large scale, the effect of one variable on disease may follow three response scenarios: the effect may be the same across the entire study area, the effect can change according to the variable value, and the effect can change depending on local specificities. Each of these scenarios impacts large-scale modeling differently.