Estimating the transfusion transmission risk of Q fever

Current Status of Q Fever and the Challenge of Outbreak Preparedness in Korea: One Health Approach to Zoonoses

Human Q fever, a zoonosis caused by Coxiella burnetii, presents with diverse clinical manifestations ranging from mild self-limited febrile illnesses to life-threatening complications such as endocarditis or vascular infection. Although acute Q fever is a benign illness with a low mortality rate, a large-scale outbreak of Q fever in the Netherlands led to concerns about the possibility of blood transfusion-related transmission or obstetric complications in pregnant women. Furthermore, a small minority (< 5%) of patients with asymptomatic or symptomatic infection progress to chronic Q fever. Chronic Q fever is fatal in 5-50% of patients if left untreated. In South Korea, Q fever in humans was designated as a notifiable infectious disease in 2006, and the number of Q fever cases has increased sharply since 2015. Nonetheless, it is still considered a neglected and under-recognized infectious disease. In this review, recent trends of human and animal Q fever in South Korea, and public health concerns regarding Q fever outbreaks are reviewed, and we consider how a One Health approach could be applied as a preventive measure to prepare for zoonotic Q fever outbreaks.

Coxiella burnetii (Q-fever) outbreak associated with non-occupational exposure in a semi-urban area of western Croatia in 2022

In March 2022, an outbreak of Q fever (Coxiella burnetii) with non-occupational exposure was confirmed in a semi-urban area in Čavle, Croatia. Veterinary and human epidemiological investigations were conducted to identify the source of the outbreak and to implement appropriate control measures. Three farms were settled next to each other near the homes of the first human cases at the end of the street. The closest farm was less than 500 meters away. These farms contained 161 adult sheep and goats. Among the animal samples analysed, all 16 goats (100%) and 24/50 sheep (48%) tested positive for C. burnetii IgM/IgG antibodies, phase I and II. One out of five sheeps' vaginal swabs were C. burnetti DNA positive. Human testing revealed 20 confirmed and three probable cases (9/23 pneumonia, 2/23 hepatitis, 21/23 fever), with three hospitalizations, and one death. Twenty-seven cases were discarded following negative laboratory results. The epidemiological investigation revealed airborne transmission as the most likely route of transmission. Multiple logistic regression analyses were used to evaluate risk factors for Q fever infection. Persons who were near the farms (≤750 m) (OR 4.5; 95% CI = 1.1-18.3) and lived in the nearest street to the farms had the highest risk of contracting Q fever (OR 3.7; 95% CI = 1.1-13.6). Decreased rainfall compared to monthly averages was recorded in the months prior to the outbreak with several days of strong wind in January preceding the outbreak. This was the largest Q fever outbreak in the county in the last 16 years, which was unexpected due to its location and non-occupational exposure. To stop the outbreak, numerous intensive biosecurity measures were implemented. The outbreak highlights the importance of urban development strategies to limit the number of animal housing near residential areas while providing regular biosecurity measures to prevent infections in livestock.

Current perspectives on the transmission of Q fever: Highlighting the need for a systematic molecular approach for a neglected disease in Africa

Q fever is a bacterial worldwide zoonosis (except New Zealand) caused by the Gram-negative obligate intracellular bacterium Coxiella burnetii (C. burnetii). The bacterium has a large host range including arthropods, wildlife and companion animals and is frequently identified in human and livestock populations. In humans, the disease can occur as either a clinically acute or chronic aetiology, affecting mainly the lungs and liver in the acute disease, and heart valves when chronic. In livestock, Q fever is mainly asymptomatic; however, the infection can cause abortion, and the organism is shed in large quantities, where it can infect other livestock and humans. The presence of Q fever in Africa has been known for over 60 years, however while our knowledge of the transmission routes and risk of disease have been well established in many parts of the world, there is a significant paucity of knowledge across the African continent, where it remains a neglected zoonosis. Our limited knowledge of the disease across the African sub-continent have relied largely upon observational (sero) prevalence studies with limited focus on the molecular epidemiology of the disease. This review highlights the need for systematic studies to understand the routes of C. burnetii infection, and understand the disease burden and risk factors for clinical Q fever in both humans and livestock. With such knowledge gaps filled, the African continent could stand a better chance of eradicating Q fever through formulation and implementation of effective public health interventions.

Assessing the Threat: Public Health

This chapter describes three methods for assessing the impact of transfusion-transmitted infections on public health. In order of increasing precision and labor intensity, these tools are:

A blueprint for a structured, qualitative inventory and report, describing the relevant characteristics of the emerging agent, which helps to make ad hoc decisions and which identifies gaps in our knowledge.

Two more sophisticated “off the shelf” methods for the quantitative analysis of threats to blood safety are mentioned: the Biggerstaff-Petersen model and the European Up-Front Risk Assessment Tool (EUFRAT). The Biggerstaff-Petersen model estimates the number of potentially infectious donations, while EUFRAT also takes into account the components prepared from donations and the efficacy of various mitigating interventions.

Finally examples of quantitative studies of specific agents are mentioned: a donor-recipient transmission study and a cost-benefit modeling study. For this kind of analysis, no standardized recipe is available.

Emerging infectious disease outbreaks: estimating disease risk in Australian blood donors travelling overseas

BACKGROUND AND OBJECTIVES

International travel assists spread of infectious pathogens. Australians regularly travel to South-eastern Asia and the isles of the South Pacific, where they may become infected with infectious agents, such as dengue (DENV), chikungunya (CHIKV) and Zika (ZIKV) viruses that pose a potential risk to transfusion safety. In Australia, donors are temporarily restricted from donating for fresh component manufacture following travel to many countries, including those in this study. We aimed to estimate the unmitigated transfusion-transmission (TT) risk from donors travelling internationally to areas affected by emerging infectious diseases.

MATERIALS AND METHODS

We used the European Up-Front Risk Assessment Tool, with travel and notification data, to estimate the TT risk from donors travelling to areas affected by disease outbreaks: Fiji (DENV), Bali (DENV), Phuket (DENV), Indonesia (CHIKV) and French Polynesia (ZIKV).

RESULTS

We predict minimal risk from travel, with the annual unmitigated risk of an infected component being released varying from 1 in 1·43 million to <1 in one billion and the risk of severe consequences ranging from 1 in 130 million to <1 in one billion.

CONCLUSION

The predicted unmitigated likelihood of infection in blood components manufactured from donors travelling to the above-mentioned areas was very low, with the possibility of severe consequences in a transfusion recipient even smaller. Given the increasing demand for plasma products in Australia, the current strategy of restricting donors returning from select infectious disease outbreak areas to source plasma collection provides a simple and effective risk management approach.

Emerging Infectious Diseases and Blood Safety: Modeling the Transfusion-Transmission Risk

While the transfusion-transmission (TT) risk associated with the major transfusion-relevant viruses such as HIV is now very low, during the last 20 years there has been a growing awareness of the threat to blood safety from emerging infectious diseases, a number of which are known to be, or are potentially, transfusion transmissible. Two published models for estimating the transfusion-transmission risk from EIDs, referred to as the Biggerstaff-Petersen model and the European Upfront Risk Assessment Tool (EUFRAT), respectively, have been applied to several EIDs in outbreak situations. We describe and compare the methodological principles of both models, highlighting their similarities and differences. We also discuss the appropriateness of comparing results from the two models. Quantitating the TT risk of EIDs can inform decisions about risk mitigation strategies and their cost-effectiveness. Finally, we present a qualitative risk assessment for Zika virus (ZIKV), an EID agent that has caused several outbreaks since 2007. In the latest and largest ever outbreak, several probable cases of transfusion-transmission ZIKV have been reported, indicating that it is transfusion-transmissible and therefore a risk to blood safety. We discuss why quantitative modeling the TT risk of ZIKV is currently problematic.

•

During the last 20 years there has been a growing awareness of the threat to blood safety from emerging infectious diseases (EIDs), a number of which are known to be, or are potentially, transfusion-transmissible.

•

The transfusion-transmission risk of EID agents can be estimated by risk modeling which can form an important part of risk assessments and inform decisions regarding risk mitigation strategies.

•

We describe and compare the methodological principles of two published risk models for estimating the transfusion transmission risk of EIDs.

•

We use Zika virus as a case study to demonstrate that reliable risk modeling for EID agents can be problematic due to the uncertainty of the input parameters.

From Q Fever to Coxiella burnetii Infection: a Paradigm Change

Coxiella burnetii is the agent of Q fever, or "query fever," a zoonosis first described in Australia in 1937. Since this first description, knowledge about this pathogen and its associated infections has increased dramatically. We review here all the progress made over the last 20 years on this topic. C. burnetii is classically a strict intracellular, Gram-negative bacterium. However, a major step in the characterization of this pathogen was achieved by the establishment of its axenic culture. C. burnetii infects a wide range of animals, from arthropods to humans. The genetic determinants of virulence are now better known, thanks to the achievement of determining the genome sequences of several strains of this species and comparative genomic analyses. Q fever can be found worldwide, but the epidemiological features of this disease vary according to the geographic area considered, including situations where it is endemic or hyperendemic, and the occurrence of large epidemic outbreaks. In recent years, a major breakthrough in the understanding of the natural history of human infection with C. burnetii was the breaking of the old dichotomy between "acute" and "chronic" Q fever. The clinical presentation of C. burnetii infection depends on both the virulence of the infecting C. burnetii strain and specific risks factors in the infected patient. Moreover, no persistent infection can exist without a focus of infection. This paradigm change should allow better diagnosis and management of primary infection and long-term complications in patients with C. burnetii infection.

Refining the risk estimate for transfusion-transmission of occult hepatitis B virus

BACKGROUND AND OBJECTIVES

We previously published a model to estimate the residual risk (RR) for occult hepatitis B infection (OBI) in the absence of universal anti-HBc testing. To incorporate new information on the epidemiology of OBI, we describe model refinements and estimate a more accurate HBV RR due to OBI in Australia.

MATERIALS AND METHODS

In our original model, the OBI risk, p(OBI), was defined by the rate of 'non-detection' by the HBV DNA screening test in use, p(NAT non-detection), and the average infectivity of blood components from OBI donors, p(transmission). We revised the model by integrating three refinements: that donations with anti-HBs levels of >10 IU/l, or donations solely for manufactured plasma products, be excluded from the risk calculation, and an updated estimate of p(transmission).

RESULTS

Refining our OBI RR model resulted in a more than 10-fold reduction in the reported RR risk to recipients from OBI in our donor population. Based on the use of a common data set, the mean OBI RR risk decreased from 1 in 374 354 donations (95% CI: 1 in 191 940-1 072 681) to 1 in 3 984 033 (95% CI: 1 in 1 146 188-65 268 257) for the refined model.

CONCLUSION

Our model refinements provide a more realistic measure of the HBV RR in the donor population. Unlike the previous model, the new model demonstrates that the risk of HBV due to OBI in the Australian blood donor population is negligible, and further potentially cost-ineffective risk management strategies are not currently warranted.

Modelling the risk of transfusion transmission from travelling donors

Background

The EUFRAT (European Up-Front Risk Assessment Tool) was developed as an online risk assessment tool (http://eufrattool.ecdc.europa.eu) to help decision-makers assess the transmission risk of emerging infectious diseases (EID) through blood transfusion. The aim of this study is to extend the methodology developed in the EUFRAT project to quantify the transfusion transmission (TT) risk from travelling donors.

Methods

A generic model for estimating the TT risk from a group of travelling donors that visited an EID risk area was developed. In addition, the new model distinguishes projected future transmissions from those that have already occurred. As an illustration the model was applied to the outbreaks of chikungunya in Italy in 2007 and Q fever in the Netherlands in 2007–2009.

Results

Formulas for calculating the travelling donors’ TT risk were derived. For the chikungunya outbreak in Italy an early intervention (at the end of week 7 after the start of the outbreak, so after only 19 % of all cases) would have been required to prevent only 41 % of all expected transmissions at that time. For Q fever, in which the transmission of chronic Q fever is considered, even at the end of the third annual outbreak’s peak 47 % of all (chronic) Q fever transmissions could still be prevented.

Conclusions

The updated model allows estimation of the infection transmission risk from travelling donors. In combination with the distinction between past and future transmissions, these estimates provide valuable information to support decisions concerning communication with the public and/or the implementation of safety interventions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-016-1452-z) contains supplementary material, which is available to authorized users.

Impact of using different blood donor subpopulations and models on the estimation of transfusion transmission residual risk of human immunodeficiency virus, hepatitis B virus, and hepatitis C virus in Zimbabwe

BACKGROUND

Various models for estimating the residual risk (RR) of transmission of infections by blood transfusion have been published mainly based on data from high-income countries. However, to obtain the data required for such an assessment remains challenging for most developing settings. The National Blood Service Zimbabwe (NBSZ) adapted a published incidence-window period (IWP) model, which has less demanding data requirements. In this study we assess the impact of various definitions of blood donor subpopulations and models on RR estimates. We compared the outcomes of two published models and an adapted NBSZ model.

STUDY DESIGN AND METHODS

The Schreiber IWP model (Model 1), an amended version (Model 2), and an adapted NBSZ model (Model 3) were applied. Variably the three models include prevalence, incidence, preseroconversion intervals, mean lifetime risk, and person-years at risk. Annual mean RR estimates and 95% confidence intervals for each of the three models for human immunodeficiency virus (HIV), hepatitis B virus (HBV), and hepatitis C virus (HCV) were determined using NBSZ blood donor data from 2002 through 2011.

RESULTS

The annual mean RR estimates for Models 1 through 3 were 1 in 6542, 5805, and 6418, respectively for HIV; 1 in 1978, 2027, and 1628 for HBV; and 1 in 9588, 15,126, and 7750, for HCV.

CONCLUSIONS

The adapted NBSZ model provided comparable results to the published methods and these highlight the high occurrence of HBV in Zimbabwe. The adapted NBSZ model could be used as an alternative to estimate RRs when in settings where two repeat donations are not available.

Re-evaluating the residual risk of transfusion-transmitted Ross River virus infection

BACKGROUND AND OBJECTIVES

Ross River virus (RRV) is an enveloped, RNA alphavirus in the same antigenic group as chikungunya virus. Australia records an annual average of 5000 laboratory-confirmed RRV infections. While RRV is currently geographically restricted to the Western Pacific, the capacity of arboviruses for rapid expansion is well established. The first case of RRV transfusion-transmission was recently described prompting a comprehensive risk assessment.

MATERIALS AND METHODS

To estimate the RRV residual risk, we applied laboratory-confirmed RRV notifications to two published models. This modelling generated point estimates for the risk of viraemia in the donor population, the risk of collecting a viraemic donation and the predicted number of infected components.

RESULTS

The EUFRAT model estimated the risk of infection in donors as one in 95 039 (one in 311 328 to one in 32 399) to one in 14 943 (one in 48 593 to one in 5094). The point estimate for collecting a RRV viraemic donation varied from one in 166 486 (one in 659 078 to one in 49 158) (annualized national risk) to one in 26 117 (one in 103 628 to one in 7729) (area of high transmission). The modelling predicted 8-11 RRV-infected labile blood components issued in Australia during a 1-year period.

CONCLUSION

Considering the uncertainty in the modelled estimates, the unknown rate of RRV donor viraemia and the low severity of any recipient RRV infection, additional risk management for RRV in Australia will initially be restricted to strengthening the messaging to donors regarding prompt reporting of any postdonation illnesses.