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Disease burden of psittacosis in the Netherlands

Published online by Cambridge University Press:  24 January 2018

B. de Gier*
Affiliation:
Centre for Epidemiology and Surveillance of Infectious Diseases, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands
L. Hogerwerf
Affiliation:
Centre for Epidemiology and Surveillance of Infectious Diseases, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands
F. Dijkstra
Affiliation:
Centre for Epidemiology and Surveillance of Infectious Diseases, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands
W. van der Hoek
Affiliation:
Centre for Epidemiology and Surveillance of Infectious Diseases, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands
*
Author for correspondence: B. de Gier, E-mail: [email protected]
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Abstract

Psittacosis (infection with Chlamydia psittaci) can have diverse presentations in humans, ranging from asymptomatic infection to severe systemic disease. Awareness of psittacosis and its presentations are low among clinicians and the general public. Therefore, underdiagnosis and thereby underestimation of the incidence and public health importance of psittacosis is very likely. We used the methodology developed for the Burden of communicable diseases in Europe toolkit of the European Centre for Disease Prevention and Control, to construct a model to estimate disease burden in disability-adjusted life years (DALYs) attributable to psittacosis. Using this model, we estimated the disease burden caused by psittacosis in the Netherlands to have been 222 DALY per year (95% CI 172–280) over the period 2012–2014. This is comparable with the amount of DALYs estimated to be due to rubella or shigellosis in the same period in the Netherlands. Our results highlight the public health importance of psittacosis and identify evidence gaps pertaining to the clinical presentations and prognosis of this disease.

Type
Short Report
Copyright
Copyright © Cambridge University Press 2018 

Psittacosis is a zoonotic infection, caused by the intracellular bacterium Chlamydia psittaci. It is best known for having its reservoir in ornamental pet birds (‘parrot fever’) but has been found in many other animal species, including in pigeons and poultry [Reference Heddema1, Reference Lagae2]. Symptoms are often of respiratory nature (pneumonia), but the infection may also remain asymptomatic, present as nonspecific febrile illness or as invasive disease such as meningitis, hepatitis or sepsis [Reference Heddema3, Reference Yung and Grayson4]. Awareness of psittacosis is generally low, both among clinicians and the general public [Reference Beeckman and Vanrompay5]. Combined with the fact that C. psittaci is often not included in routine diagnostic panels, underdiagnosis of psittacosis is likely to occur [Reference Spoorenberg6] and the true public health importance of psittacosis is largely unknown.

Disease burden estimations combine occurrence and severity of a disease to estimate (and compare) health impact. Rankings of diseases by burden can be useful to aid policy prioritisation. Therefore, burden estimations are also able to shed more light on the public health importance of lesser-known diseases, such as psittacosis. The European Centre for Disease Prevention and Control (ECDC)-commissioned Burden of Communicable Diseases in Europe (BCoDE) project developed an incidence-based and pathogen-based methodology specifically to estimate the burden of infectious disease in disability-adjusted life years (DALY) [Reference Mangen7]. DALYs are the sum of years of life lost (YLL) due to mortality and the years of life lived with disability (YLD) which measures morbidity. The YLD is the product of incidence, duration and severity, the latter being defined by a ‘disability weight’ between 0 (perfect health) and 1 (death). The ECDC has developed a toolkit to enable countries to estimate and compare the burden of 38 infectious diseases by this methodology [8]. However, a model for psittacosis was not yet included. Using the BCoDE methodology, we developed a disease model for psittacosis to estimate its disease burden in the Netherlands, which can also be used by other countries.

We constructed an ‘outcome tree’ of the clinical courses of confirmed psittacosis patients based on a review of the literature (Fig. 1). We searched Medline for studies describing psittacosis cases or outbreaks, wherein descriptions and frequencies of symptoms were listed for laboratory-confirmed cases. We further asked experts if they knew about relevant data or publications for our purpose. Four studies were identified that described the clinical presentations of psittacosis infections [Reference Heddema3, Reference Yung and Grayson4, Reference Laroucau9, Reference Branley10]. To estimate the distribution of the distinct clinical features (‘health states’) within acute symptomatic infections, we performed a meta-analysis on data extracted from the literature using the package ‘metaprop’ in STATA version 13·0. Based on the results of our meta-analysis (Fig. S1), we assumed 5.6% of symptomatic infections to cause invasive illness (e.g. hepatitis, sepsis, meningitis); 45.0% to present as pneumonia and the remaining 49.4% to be a nonspecific febrile illness. No studies were found reporting a case fatality of psittacosis. Therefore, we performed a meta-analysis of two studies on outcomes of atypical pneumoniae in Dutch hospitalised patients (one for acute Q fever, one for atypical pneumonia), see Fig. S2 [Reference Kampschreur11, Reference Raeven12]. The result of this meta-analysis was a case fatality of 1.44% (95% CI 0.70–2.40%), which we modelled as β (10.9, 743) and multiplied by the proportion hospitalised psittacosis patients (modelled as β (202, 101)), to adjust for the fact that the studies contributing to the case fatality estimate were in hospitalised patients. This resulted in an overall case fatality estimate of 0.93% (95% CI 0.48–1.62%) We applied the case fatality estimate only to patients age 50 and older, as both studies found mortality mainly in adults above 50 years old [Reference Kampschreur11, Reference Raeven12]. We did not find enough evidence for more health state-specific case fatality estimates nor could we find evidence to justify further age- or sex-specific transition probabilities.

Fig. 1. Outcome tree of psittacosis disease progression model.

We applied disability weights recently estimated specifically for Europe [Reference Haagsma13]. Duration of pneumonia was set to 2 weeks, nonspecific febrile illness was assumed to last 5 days and invasive illness between 10 and 14 days (in accordance with the invasive pneumococcal disease in the BCoDE model). We assumed a disability weight of 0.051 (acute infectious disease episode, moderate) for nonspecific febrile illness [Reference Haagsma13]. For pneumonia, the disability weight of a severe acute infectious disease episode was assumed (0.125), as in the (healthcare-associated) pneumonia model. Invasive illness was given the disability weight of 0.655, defined for an intensive care unit admission, as was done for the invasive pneumococcal disease model by ECDC.

While psittacosis is a notifiable infectious disease in the Netherlands, we expect the notified cases to be an incomplete record of all psittacosis infections, due to underdiagnosis. To estimate a multiplication factor to apply to the notified cases to account for underestimation, we used the results of a systematic review and meta-analysis of the proportion of C. psittaci diagnoses in studies among community-acquired pneumonia (CAP) patients. This study is further described in reference [Reference Hogerwerf14]. In short, the result of this meta-analysis estimated 1.03% (95% CI 0.79–1.30%) C. psittaci infections in CAP patients. Table 1 shows the calculations by which we estimated the multiplication factor of 22.7 (95% CI: 12.2–64.6) to adjust for underestimation of the psittacosis incidence by national notifications. In other words, we estimate 4.4% (95% CI 1.6–8.2%) of symptomatic cases to be notified in the Netherlands. Calculations were performed in R [15] and uncertainty was propagated using Monte Carlo simulation; specifically 1 000 000 random draws were made from the defined distributions for each variable.

Table 1. Steps in the estimation of multiplication factor for underestimation of a total number of psittacosis infections in the Netherlands by national notification registry

CAP, community-acquired pneumonia.

Average annual psittacosis notifications in 2012–2014 per age and sex were used as input. We ran the model in ECDC BCoDE toolkit version 1.2, with 10 000 iterations and no time discounting or age weighting. The model-based age- and sex-specific remaining life expectancies as in the 2010 Global Burden of Disease study was used and the average age distribution of the Dutch population in 2012–2014.

Our model estimated 1640 acute symptomatic cases of psittacosis and 9.7 deaths to have occurred annually in the Netherlands in 2012–2014. Men were more often affected than women, based on the notification data (61% vs. 39%). The estimated annual disease burden caused by psittacosis in the Netherlands was 222 DALY (95% CI 172–280). This corresponds to 1.32 (95% CI 1.02–1.67) DALY per 100.000 population. The disease burden was mainly due to mortality: 214 (95% CI 165–271) YLL and 7.6 (95% CI 6.5–8.7) YLD per year were estimated. The average DALY per case was 0.13 (95% CI 0.11–0.16). As mortality was only included in the model for patients above the age of 50, the disease burden was largely found in this group. Sixty-one per cent of notifications, concerned patients in this age category. When a time discount rate of 3% is applied, we estimate the psittacosis disease burden for 2012–2014 at 162 DALY/year (95% CI 128–205).

Aside from providing a first psittacosis disease burden estimation, this study has highlighted some evidence gaps. There is little information on clinical presentation of C. psittaci infection and one of four studies that we identified was published almost 30 years ago. However, as our review was not systematic, some published evidence may have been missed. We aimed to be conservative with our assumptions. However, the estimate of 67% hospitalisation of psittacosis cases may be too high. The evidence is lacking on mortality from psittacosis, although sporadic published reports and national notification data are in concordance with our estimate of around 1% mortality in older adults [Reference Petrovay and Balla16]. Since our disease burden estimate is mainly attributable to years of life lost, more evidence on psittacosis mortality is needed to better estimate disease burden. Further, long-term sequelae (such as fatigue) after acute psittacosis infection have not been described but may occur as with other (atypical) pneumoniae. A recent study showed a lower health-related quality of life in elderly up to 12 months after admission for community-acquired pneumonia compared with matched controls [Reference Mangen17]. Also, the large multiplication factor for underestimation highlights the uncertainty regarding the actual number of psittacosis patients in the Netherlands. Aside from surveillance or burden estimation purposes, underdiagnosis of this zoonosis is a serious issue as this may delay or even prevent appropriate therapy, as the prevailing professional guidelines recommend beta-lactam antibiotic therapy for the clinically diagnosed CAP, which is not effective against C. psittaci [Reference Spoorenberg6]. Also, undiagnosed psittacosis cases represent missed opportunities for source tracing and elimination to prevent further cases.

Our estimated psittacosis disease burden of 222 DALY/year is comparable with those of rubella (222 DALY/year) and shigellosis (179 DALY/year) during the same period (2012–2104), which are also undiscounted estimates [Reference Bijkerk18]. According to our estimations, more than 1500 symptomatic psittacosis patients remained undiagnosed yearly in the Netherlands in 2012–2014. These results warrant increased awareness among clinicians and the general public of this zoonosis and possibly prioritisation of policies aimed at reducing the psittacosis disease burden. With the model we constructed and the parameters reported here, other countries may assess their psittacosis disease burden as well. The model is hereby available in a format that can be adjusted and imported into the ECDC BCoDE toolkit (Supplementary file 1).

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0950268817003065.

Acknowledgements

We wish to acknowledge the valuable contributions of Barend Baan and Scott McDonald to this study, as well as constructive feedback from Marianne van der Sande and Jaap van Dissel (all RIVM). This study was funded by the Dutch Ministry of Health, Welfare and Sport and from the Plat4m-2Bt-psittacosis project, granted by ZonMw, the Netherlands Organization for Health Research and Development (project number 522001002).

Declaration of Interest

None.

Footnotes

*

These authors contributed equally to this work.

References

1.Heddema, ER, et al. (2015) Typing of Chlamydia psittaci to monitor epidemiology of psittacosis and aid disease control in the Netherlands, 2008 to 2013. Euro Surveillance 20(5), 21026.Google Scholar
2.Lagae, S, et al. (2014) Emerging Chlamydia psittaci infections in chickens and examination of transmission to humans. Journal of Medical Microbiology 63(Pt 3), 399407.Google Scholar
3.Heddema, ER, et al. (2006) An outbreak of psittacosis due to Chlamydophila psittaci genotype A in a veterinary teaching hospital. Journal of Medical Microbiology 55(Pt 11), 15711575.Google Scholar
4.Yung, AP and Grayson, ML (1988) Psittacosis--a review of 135 cases. Medical Journal of Australia 148(5), 228233.Google Scholar
5.Beeckman, DS and Vanrompay, DC (2009) Zoonotic Chlamydophila psittaci infections from a clinical perspective. Clinical Microbiology and Infection 15(1), 1117.Google Scholar
6.Spoorenberg, SM, et al. (2016) Chlamydia psittaci: a relevant cause of community-acquired pneumonia in two Dutch hospitals. Netherlands Journal of Medicine 74(2), 7581.Google Scholar
7.Mangen, MJ, et al. (2013) The pathogen- and incidence-based DALY approach: an appropriate [corrected] methodology for estimating the burden of infectious diseases. PloS ONE 8(11), e79740.Google Scholar
8.Anon. (2015) ECDC BCoDE toolkit [software application]: Version 1.2. In. Stockholm: European Centre for Disease Prevention and Control.Google Scholar
9.Laroucau, K, et al. (2015) Outbreak of psittacosis in a group of women exposed to Chlamydia psittaci-infected chickens. Euro Surveillance 20(24):pii=21155.Google Scholar
10.Branley, JM, et al. (2014) Clinical features of endemic community-acquired psittacosis. New Microbes and New Infections 2(1), 712.Google Scholar
11.Kampschreur, LM, et al. (2010) Acute Q fever related in-hospital mortality in the Netherlands. Netherlands Journal of Medicine 68(12), 408413.Google Scholar
12.Raeven, VM, et al. (2016) Atypical aetiology in patients hospitalised with community-acquired pneumonia is associated with age, gender and season; a data-analysis on four Dutch cohorts. BMC Infectious Diseases 16, 299.Google Scholar
13.Haagsma, JA, et al. (2015) Assessing disability weights based on the responses of 30,660 people from four European countries. Population Health Metrics 13, 10.Google Scholar
14.Hogerwerf, L, et al. (2017) Chlamydia psittaci (psittacosis) as a cause of community-acquired pneumonia: a systematic review and meta-analysis. Epidemiology and Infection, 145(15):30963105.Google Scholar
15.Anon. R (2017) A language and environment for statistical computing. In. version 1.0.143 ed. Vienna, Austria: R Core team.Google Scholar
16.Petrovay, F and Balla, E (2008) Two fatal cases of psittacosis caused by Chlamydophila psittaci. Journal of Medical Microbiology 57(Pt 10), 12961298.Google Scholar
17.Mangen, MJ, et al. (2017) The impact of community-acquired pneumonia on the health-related quality-of-life in elderly. BMC Infectious Diseases 17(1), 208.Google Scholar
18.Bijkerk, P, et al. (2016) State of Infectious Diseases in the Netherlands, 2015. Bilthoven: National Institute for Public Health and the Environment (RIVM).Google Scholar
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Fig. 1. Outcome tree of psittacosis disease progression model.

Figure 1

Table 1. Steps in the estimation of multiplication factor for underestimation of a total number of psittacosis infections in the Netherlands by national notification registry

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