https://orcid.org/0000-0003-2643-4213
Figures
Abstract
Background
Understanding the risk of chikungunya virus (CHIKV) infection and rheumatic sequelae across populations, including travelers and the military, is critical. We leveraged healthcare delivery data of over 9 million U.S. Military Health System (MHS) beneficiaries to identify cases, and sampled controls, to estimate the risk of post-CHIKV rheumatic sequelae.
Methodology/principal findings
MHS beneficiary CHIKV infections diagnosed 2014–2018 were identified from the Disease Reporting System internet, TRICARE Encounter Data Non-Institutional, and Comprehensive Ambulatory/Professional Encounter Record systems. Non-CHIKV controls were matched (1:4) by age, gender, beneficiary status, and encounter date. The frequency of comorbidities and incident rheumatic diagnoses through December 2018 were derived from International Classification of Diseases codes and compared between cases and controls. Poisson regression models estimated the association of CHIKV infection with rheumatic sequelae. We further performed a nested case-control study to estimate risk factors for post-CHIKV sequelae in those with prior CHIKV. 195 CHIKV cases were diagnosed between July 2014 and December 2018. The median age was 42 years, and 43.6% were active duty. 63/195 (32.3%) of CHIKV cases had an incident rheumatic diagnosis, including arthralgia, polyarthritis, polymyalgia rheumatica, and/or rheumatoid arthritis, compared to 156/780 (20.0%) of controls (p < 0.001). CHIKV infection remained associated with rheumatic sequelae (aRR = 1.579, p = 0.008) after adjusting for prior rheumatic disease and demography. Those with rheumatic CHIKV sequelae had a median 7 healthcare encounters (IQR 3–15). Among CHIKV infections, we found no association between post-CHIKV rheumatic sequelae and demography, service characteristics, or comorbidities.
Conclusions/significance
CHIKV infection is uncommon but associated with rheumatic sequelae among MHS beneficiaries, with substantial healthcare requirements in a proportion of cases with such sequelae. No demographic, clinical, or occupational variables were associated with post-CHIKV rheumatic sequelae, suggesting that prediction of these complications is challenging in MHS beneficiaries. These findings are important context for future CHIKV vaccine decision making in this and other populations.
Author summary
We examined U.S. Military Health System (MHS) healthcare delivery data to identify the likelihood of rheumatic complications after chikungunya virus (CHIKV) infection. Overall, CHIKV infections were rare in the MHS, with 195 cases found in the records between 2014 and 2018 (a period which encompassed the peak of the CHIKV epidemic in the Americas). Of these, about 32% received a rheumatic diagnosis after infection, including arthralgia, polyarthritis, polymyalgia rheumatica, and rheumatoid arthritis. Patients who had a rheumatic diagnosis had on average 7 healthcare encounters for their post-CHIKV rheumatic complication, and a quarter had more than 15 healthcare encounters. We did not find any demographic, clinical, or occupational characteristics associated with developing rheumatic complications after CHIKV, suggesting that predicting rheumatic complications from CHIKV may be challenging in MHS beneficiaries. These findings may provide important context for decisions about implementing an approved chikungunya vaccine to military servicemembers and other MHS beneficiaries.
Citation: Pollett S, Hsieh H-C, Lu D, Grance M, Richard S, Nowak G, et al. (2024) The risk and risk factors of chikungunya virus infection and rheumatological sequelae in a cohort of U.S. Military Health System beneficiaries: Implications for the vaccine era. PLoS Negl Trop Dis 18(8): e0011810. https://doi.org/10.1371/journal.pntd.0011810
Editor: Fernando Lopes, Broad Institute Harvard: Broad Institute, UNITED STATES OF AMERICA
Received: November 22, 2023; Accepted: July 1, 2024; Published: August 5, 2024
This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Data Availability: Data for this study are available from the Infectious Disease Clinical Research Program (IDCRP), headquartered at the Uniformed Services University of the Health Sciences (USU), Department of Preventive Medicine and Biostatistics. Review by the USU Institutional Review Board is required for use of the data used in this protocol. Furthermore, the data set includes Military Health System data collected under a Data Use Agreement that requires accounting for uses of the data. Data requests may be sent to: Address: 6270A Rockledge Drive, Suite 250, Bethesda, MD 20817. Email: contactus@idcrp.org.
Funding: The protocol was executed by the Infectious Disease Clinical Research Program (IDCRP), a Department of Defense program executed by the Uniformed Services University of the Health Sciences through a cooperative agreement by the Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc.. This project has been funded in part by the National Institute of Allergy and Infectious Diseases at the National Institutes of Health, under an interagency agreement (Y1-AI-5072) (SP, DL, MG, HC-H); and the Military Infectious Diseases Research Program (DL, MG, HC-H). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Chikungunya virus (CHIKV) is a mosquito-borne alphavirus belonging to the Togaviridae family [1]. The ecology of CHIKV is characterized by a sylvatic cycle involving non-human primates and arboreal Aedes species and urban human-to-human transmission cycles involving the A. aegypti and A. albopictus vectors [1]. While CHIKV is defined by a single serotype, multiple genotypes have evolved with global geographic expansion including the Asian and descendant Asian-Caribbean lineages, and East/Central/South African and Indian Ocean lineages [1–3].
The 2013–2015 neotropical epidemic in the Americas involved over 1.6 million suspected or confirmed CHIKV cases [4]. While cases rapidly declined after the initial neotropical pandemic, there is an ongoing substantive CHIKV burden in the Americas in addition to ongoing circulation in Africa [5,6] and Asia [7,8]. Recently, the Pan American Health Organization issued an alert indicating the geographic range of CHIKV has expanded in the Americas, with notable resurgence in certain regions of Latin America [9–11].
Acute CHIKV infection illness is characterized by a high symptomatic-to-asymptomatic ratio, with clinical features including an abrupt onset of high fever, polyarthralgia, backache, headache, and fatigue [12]. Atypical acute CHIKV illness manifestations (e.g., acute encephalitis) are rare, potentially severe, and more often occur in the extremes of age and in those with underlying comorbidities [12–17]. Diagnosis of CHIKV infection relies on blood polymerase chain reaction (PCR) within the first week of illness and serology thereafter [18]. Management of acute CHIKV is generally supportive, with fluid replacement, analgesia and avoidance of non-steroidal anti-inflammatory drugs until dengue has been excluded as a differential diagnosis [19]. There are limited preventive medical countermeasures available for CHIKV aside from avoidance of vectors in endemic transmission regions [19]. Advanced vaccine development has been challenging due to the unpredictable nature of CHIKV outbreaks [20]. However, CHIKV vaccine U.S. Food and Drug Administration licensure recently occurred using a serological correlate of protection, and other vaccines may be licensed in the future [21].
The rheumatological manifestations of CHIKV may be categorized by timing and clinical phenotype [22]. Acute CHIKV arthralgia is frequently reported and mostly occurs in mostly peripheral joints with a symmetrical pattern, although large joints can be affected [22]. Joint swelling and synovitis often accompanies this acute polyarthralgia; functional impairment during this acute phase is common due debilitating pain [22]. Chronic rheumatological manifestations typically involve the joints affected in acute CHIKV arthralgia [22]. Estimates on the frequency of persistent post-acute manifestations (predominantly arthralgia or arthritis) vary significantly, with metanalysis estimates as high as 43% at 3 months, 21% at 12 months, and 14% at 18 months after initial CHIKV illness onset [22–24]. Pathogenesis studies have suggested that persistent host inflammation, rather than persistent synovial viral replication, plays a key role in post-CHIKV arthralgia [25,26]. There is currently a wide variation in clinical management for chronic post-CHIKV sequelae [15] but post-acute CHIKV arthropathy is severe enough in some to warrant the use of biological or disease-modifying antirheumatic drugs [27].
While those residing in CHIKV endemic regions experience the highest burden of this arbovirus, travelers and the deploying military are also significant stakeholders for understanding the risk of CHIKV infection and post-CHIKV sequelae. There is limited published data on the burden of CHIKV in U.S. Military Health System (MHS) beneficiaries [28,29] and none define the risk and risk factors of post-acute CHIKV sequelae in this population. Understanding the risk and risk factors of CHIKV and CHIKV sequelae is important for clinical prognostication and may support cost-effectiveness analyses for vaccine policy with current and potential future licensed vaccines; such findings may be generalizable to traveler populations also.
The objectives in this study were to characterize incident CHIKV cases diagnosed in the MHS between 2005 and 2018 and to describe the risk and risk factors of acute and chronic post-CHIKV rheumatological sequelae in CHIKV cases compared to matched controls. Here, we leveraged a virtual cohort derived from over 9.5 million MHS beneficiaries, with follow-up through December 2018.
Methods
Ethics statement
This protocol was reviewed and approved for execution by the Institutional Review Board of the Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America.
Population, setting and identification of CHIKV infections and matched controls
The MHS serves approximately 9.5 million beneficiaries, including active duty servicemembers, retirees and dependents. This includes care delivered within the United States, U.S. Territories (including Puerto Rico, Guam, and the U.S. Virgin Islands), and in beneficiaries located other countries.
For this study, we identified deduplicated unique CHIKV cases in MHS beneficiaries via multiple data streams from 2005 through 2018, including: (i) clinical microbiology lab (serology and PCR) results from Disease Reporting System internet (DRSi)/EpiData Center, (ii) International Classification of Diseases, 10th Revision (ICD-10) code A92.0 CHIKV disease entries from TRICARE Encounter Data Non-Institutional (TEDNI), and (iii) ICD-10 code A92.0 CHIKV disease from Comprehensive Ambulatory/Professional Encounter Record (CAPER). The treatment locations of cases were inferred by clinical provider ZIP code. To estimate the risk of post-CHIKV rheumatological sequalae, CHIKV negative MHS beneficiary controls were matched (4:1) with CHIKV positive beneficiaries by age group, gender, date of healthcare encounter (+/- 1 month), and beneficiary status at the time of matching healthcare encounter. Controls were randomly selected within these matching strata.
Demographic, post-CHIKV diagnosis and comorbidity data abstraction from the electronic medical record
Demographic ICD-9 and ICD-10 code data were abstracted from cases and controls (using Armed Forces Health Longitudinal Technology Application (AHLTA) and the Composite Health Care System (CHCS)). The sequelae of interest were any rheumatologic disorders (Table A in S1 Text for ICD-9 and ICD-10 codes). Co-morbidity was defined as a condition/disorder (including rheumatological) which pre-existed before the time of the first CHIKV infection diagnosis (or first matched healthcare encounter of the time-matched control). We defined post-CHIKV rheumatological complications as new post-CHIKV rheumatological diagnoses with a first onset at or after the first CHIKV diagnosis (or the healthcare encounter used for matching for controls without CHIKV). Due to the typically rapid onset of arthritis in CHIKV, and because diagnosis of CHIKV may occur upon presentation to clinical care with subacute or chronic rheumatological symptoms, we did not include a latency period between CHIKV diagnosis date and date of rheumatological diagnoses.
When a pre-CHIKV rheumatological and post-CHIKV rheumatological diagnosis mapped to the same ICD code, we further adjudicated a pre-existing rheumatological diagnosis from a new post-CHIKV complication using DX_DESC-level diagnosis coding (Agency for Healthcare Research and Quality Clinical Classifications Software system code). A similar approach was taken for controls without CHIKV.
Statistical analysis
Demographic, clinical, and occupational characteristics of cases and controls were summarized. The frequency of rheumatological sequelae were compared in those with CHIKV infection (“cases”) and without CHIKV (“controls”). Multivariate Poisson regression on matched MHS beneficiaries with CHIKV infection and without CHIKV infection was used to estimate the association between CHIKV infection and rheumatological sequelae, with further analysis estimating the risk of CHIKV infection on short-term (<3 months) versus long-term (≥3 months) rheumatological complications, adjusting for pre-existing rheumatological comorbidities and demography. Unadjusted and adjusted risk ratios were presented. Finally, among those with CHIKV infections, we performed a nested case-control study comparing those with and without rheumatological sequelae in order to identify risk factors for developing post-CHIKV rheumatological sequelae. Unadjusted and adjusted odds ratios were presented.
All p values were two-sided, with an alpha significance threshold of 0.05. Analyses were conducted using SAS software (version 9.4; SAS).
Results
We identified 195 unique CHIKV cases diagnosed in the MHS between July 2014 and December 2018 (Fig A in S1 Text). The most frequent locations of clinical encounters were in Puerto Rico, Texas, and California, but these reflect provider ZIP codes of diagnoses (including potential diagnoses made after deployments or other beneficiary travel) and do not necessarily reflect the location where the cases acquired CHIKV infections (Fig 1). Our finding of the majority of cases being diagnosed in Puerto Rico was similar to prior studies in MHS beneficiaries [29,30]. Time series of all MHS CHIKV cases (by month) indicated the peak of MHS CHIKV cases occurred in late 2014 during the peak year of the Americas CHIKV epidemic.
The median age of CHIKV cases was 42 years (IQR 31–54 years), 52.8% were male, and 43.6% were active duty servicemembers (Table 1). Compared to age, gender, beneficiary status, and healthcare encounter-matched controls, cases differed from controls with respect to race (p < 0.001). White, Asian/Pacific Islander, and Other race categories were more common in CHIKV cases compared to controls. Among active duty CHIKV cases, we noted that Army service and enlisted rank were most common; the frequency of these categories were more common than matched controls (p < 0.001; Table 1). CHIKV cases had a higher frequency of all measured comorbidities compared to matched controls (p < 0.001; Table 2).
We noted 63/195 (32.3%) of CHIKV cases had an incident post-CHIKV rheumatological diagnosis, compared to 156/780 (20.0%) of controls (p = 0.0002) (Table 3). Osteoarthritis, rheumatoid arthritis and related diagnoses (including inflammatory polyarthropathy), and non-traumatic joint disorder associated categories (including unspecified arthropathy, polyarthralgia and polyarthritis) were noted with statistically significant higher frequency in post-CHIKV cases versus controls (Tables 3 and B in S1 Text).
Compared to controls, CHIKV infection was associated with post-infection rheumatological diagnoses (aRR = 1.579, 95% CI 1.125–2.215, p = 0.008) after adjusting for the presence of any prior pre-CHIKV rheumatological diagnoses, service status, age, sex, and race (Table 4). The magnitude of this effect size was larger when the outcome was stratified into short-term (≤3 month) post-CHIKV rheumatological diagnoses versus long-term (diagnosis recurred beyond 3 months post-CHIKV infection) rheumatic sequelae (aRR = 4.093, p = 0.008, short-term sequelae; aRR = 1.482, p = 0.021 long-term sequelae, respectively) (Table 5). Those with post-CHIKV rheumatological incident diagnoses had a median 7 healthcare encounters for rheumatological diagnoses (IQR 3–15, range 1–33) through the period of observation.
Among those with CHIKV infections, we found no association between post-CHIKV rheumatic sequelae and age, sex, race, active-duty status, or pre-existing comorbidities. Service branch was associated with post-CHIKV rheumatological sequelae, but this was not statistically significant (Table 6).
Discussion
Understanding the risk of CHIKV infection and complications in deploying U.S. military servicemembers and other MHS beneficiaries is important, particularly with recent and upcoming possible further CHIKV vaccine licensure. We found a very low number of CHIKV cases identified in the MHS, despite this study period covering the peak CHIKV epidemic in the Americas and leveraging data from about 9.5 million beneficiaries. Our findings correlate with low number of CHIKV infections in other U.S. MHS studies, although such studies were either smaller, earlier in the CHIKV epidemic and/or relied on varying electronic medical record (eMR) data sources [28,31]. Additionally, our findings correlate with a recent post-deployment serology study of 1500 deployments to South America and Puerto Rico with a low post-deployment seropositivity rate of 1.7% (highest in those serving in Puerto Rico) [32]. Our findings further agree with studies in other armed forces which also note a low frequency of CHIKV infections [28].
These low frequencies of infection may be attributed to effective personal mosquito avoidance or heterogeneity in risk exposure (for example, based on deployment role) when deployed or activated in CHIKV endemic countries or territories. Among CHIKV infections in servicemembers, we noted higher frequency Army service and enlisted ranks compared to matched servicemember controls without CHIKV; these groups have previously been noted at higher risk for other arboviruses [33,34]. While the location of diagnosis may not reflect where the infection was acquired, the highest number of cases were diagnosed in Puerto Rico is consistent with the known high transmission of CHIKV during the neotropical epidemic [35].
While the overall number of identified infections was very low, we found a substantive risk of post-CHIKV rheumatological complications. We noted a considerable burden of disease with a median 7 healthcare encounters for this complication, and 25% of these individuals had between 15 and 33 further encounters through the period of observation. These findings highlight that, while CHIKV infections are overall rare in MHS beneficiaries, patient morbidity in complicated CHIKV cases can be substantial, as noted in non-MHS studies [22].
The overall low number of CHIKV infections limited statistical power for examining risk factors for post-CHIKV sequelae. We found a non-statistically significant trend toward service branch having a differential risk of rheumatic complications, but no other predictors were noted, including pre-existing comorbidities. Further study of cumulative CHIKV infections in MHS-based virtual cohorts over time may identify clearer risk factors for this complication, and this may assist in more precise prognostication of CHIKV cases in the MHS. As this study comprises the largest number of CHIKV infections in any military-related population, we conclude that prediction of which MHS CHIKV cases may progress to complicated rheumatological sequelae remains challenging.
There were several strengths to this study. The use of the MHS includes a substantive number of beneficiaries who deploy or are stationed in CHIKV endemic regions and allowed for follow-up of cases to determine post-acute complications. We derived CHIKV cases from a range of eMR data sources, including clinical microbiology laboratory results, and analyzed a greater number of infections than prior MHS based studies [28–31]. Our study limitations included the use of ICD codes to diagnose CHIKV and post-CHIKV complications; prior evaluations of CHIKV ICD diagnosis coding have noted imperfect specificity [31] and this study was unable to perform chart adjudications. Conversely, CHIKV diagnoses may have been missed in some clinical presentations, and not all cases may have presented to care (including during deployments).
Future directions include studies to examine for non-rheumatological CHIKV sequelae such as neurocognitive complications, mood, and long-term functional impact (for example, [36,37]). Finally, studies could leverage sera routinely collected from the U.S. military servicemembers and used for arboviral research (i.e., the Department of Defense Sera Repository [32–34]) to identify prognostic and treatment related biomarkers for those beneficiaries with persistent post-CHIKV sequelae, as well as enabling ongoing serosurveillance of the risk and risk factors of CHIKV in deployed military, particularly during an era of increasing CHIKV risk in the Americas [9].
Disclaimer
The contents of this publication are the sole responsibility of the author(s) and do not necessarily reflect the views, opinions, or policies of Uniformed Services University of the Health Sciences; the Department of Defense; the Departments of the Army, Navy, or Air Force; the Defense Health Agency; the National Institutes of Health, the Department of Health and Human Services or the Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc. Mention of trade names, commercial products, or organizations does not imply endorsement by the U.S. government. The investigators have adhered to the policies for protection of human subjects as prescribed in 45 CFR 46.
Supporting information
S1 Text. Fig A.
Chikungunya virus case identification from U.S. Military Health System electronic medical record systems. TEDNI–TRICARE Encounter Data Non-Institutional; CAPER–Comprehensive Ambulatory/Professional Encounter Record. Table A. International Classification of Diseases, 9th Revision (ICD-9) and ICD-10 codes (including cross-walked ICD-9 codes) used to identify rheumatological healthcare encounters in cases and controls. Table B. Long description of rheumatological healthcare encounters by chikungunya virus (CHIKV) infection status.
https://doi.org/10.1371/journal.pntd.0011810.s001
(DOCX)
References
- 1. Weaver SC, Osorio JE, Livengood JA, Chen R, Stinchcomb DT. Chikungunya virus and prospects for a vaccine. Expert Rev Vaccines. 2012;11(9): 1087–1101. pmid:23151166
- 2. Weaver SC, Forrester NL. Chikungunya: Evolutionary history and recent epidemic spread. Antiviral Res. 2015;120: 32–39. pmid:25979669
- 3. Rezza G, Weaver SC. Chikungunya as a paradigm for emerging viral diseases: Evaluating disease impact and hurdles to vaccine development. PLoS Negl Trop Dis. 2019;13(1): e0006919. pmid:30653504
- 4.
54th Directing Council. Report on chikungunya virus transmission and its impact in the region of the Americas. 67th Session of the Regional Committee of WHO for the Americas; September 28 to October 2, 2015; Washington, DC: Pan American Health Organization and World Health Organization Regional Office for the Americas. Available from: https://www3.paho.org/hq/dmdocuments/2015/CD54-INF-3-e.pdf
- 5. Ushijima Y, Abe H, Mbadinga MJVM, Ondo GN, Bikangui R, Agnandji ST, et al. Re-emergence of dengue, chikungunya, and Zika viruses in 2021 after a 10-year gap in Gabon. IJID Reg. 2022;5: 68–71. pmid:36200059
- 6. Asaga Mac P, Airiohuodion PE, Yako AB, Makpo JK, Kroeger A. The seroprevalence and hidden burden of chikungunya endemicity and malaria mono- and coinfection in Nigeria. Int J Environ Res Public Health. 2022;19(15): 8896. pmid:35897268
- 7. Bettis AA, L’Azou Jackson M, Yoon IK, Breugelmans JG, Goios A, Gubler DJ, et al. The global epidemiology of chikungunya from 1999 to 2020: A systematic literature review to inform the development and introduction of vaccines. PLoS Negl Trop Dis. 2022;16(1): e0010069. pmid:35020717
- 8.
Pan American Health Organization, World Health Organization. Cases of chikungunya virus disease. 2023. Available from: https://www3.paho.org/data/index.php/en/mnu-topics/chikv-en/550-chikv-weekly-en.html
- 9.
Centers for Disease Control and Prevention. Increased chikungunya virus activity in Paraguay and associated risk to travelers. 2023. Available from: https://emergency.cdc.gov/han/2023/han00487.asp
- 10.
Pan American Health Organization, World Health Organization. Epidemiological alert: Chikungunya increase in the region of the Americas. 2023. Available from: https://www.paho.org/en/documents/epidemiological-alert-chikungunya-increase-region-americas
- 11.
Pan American Health Organization, World Health Organization. Epidemiological alert: Increase in cases and deaths from chikungunya in the region of the Americas. 2023. Available from: https://www.paho.org/en/documents/epidemiological-alert-increase-cases-and-deaths-chikungunya-region-americas
- 12.
Centers for Disease Control and Prevention. Clinical evaluation and disease. 2023. Available from: https://www.cdc.gov/chikungunya/hc/clinicalevaluation.html
- 13. de Morais Alves Barbosa Oliveira R, Kalline de Almeida Barreto F, Praça Pinto G, Timbó Queiroz I Montenegro de Carvalho Araújo F, Wanderley Lopes K, et al. Chikungunya death risk factors in Brazil, in 2017: A case-control study. PLoS One. 2022;17(4): e0260939. pmid:35389992
- 14. Sharp TM, Keating MK, Shieh WJ, Bhatnagar J, Bollweg BC, Levine R, et al. Clinical characteristics, histopathology, and tissue immunolocalization of chikungunya virus antigen in fatal cases. Clin Infect Dis. 2021;73(2): e345–e354. pmid:32615591
- 15. Webb E, Michelen M, Rigby I, Dagens A, Dahmash D, Cheng V, et al. An evaluation of global Chikungunya clinical management guidelines: A systematic review. EClinicalMedicine. 2022;54: 101672. pmid:36193172
- 16. Pescarini JM, Rodrigues M, Paixão ES, Cardim L, Brito CAA, Costa MDCN, et al. Dengue, Zika, and chikungunya viral circulation and hospitalization rates in Brazil from 2014 to 2019: An ecological study. PLoS Negl Trop Dis. 2022;16(7): e0010602. pmid:35895718
- 17. Chee YS, Ahamad Fouzi N, Chong YM, Sam IC, Chan YF, Chua CL, et al. Chikungunya encephalopathy and pneumonia in a young infant presenting with septic shock. J Paediatr Child Health. 2022;58(8): 1468–1471. pmid:35175651
- 18.
Centers for Disease Control and Prevention. Diagnostic testing. 2023. Available from: https://www.cdc.gov/chikungunya/hc/diagnostic.html
- 19.
Centers for Disease Control and Prevention. Treatment and Prevention. 2023. Available from: https://www.cdc.gov/chikungunya/hc/treatment-prevention.html
- 20. Tran QM, Soda J, Siraj A, Moore S, Clapham H, Perkins TA. Expected endpoints from future chikungunya vaccine trial sites informed by serological data and modeling. Vaccine. 2023;41(1): 182–192. pmid:36424258
- 21.
Hills S. Overview of chikungunya and chikungunya vaccines. Meeting of the Advisory Committee on Immunization Practices (ACIP); October 19–20, 2022; Atlanta, Georgia: Centers for Disease Control and Prevention.
- 22. Suhrbier A. Rheumatic manifestations of chikungunya: Emerging concepts and interventions. Nat Rev Rheumatol. 2019;15(10): 597–611. pmid:31481759
- 23. Rodríguez-Morales AJ, Cardona-Ospina JA, Urbano-Garzón SF, Hurtado-Zapata JS. Prevalence of post-chikungunya infection chronic inflammatory arthritis: A systematic review and meta-analysis. Arthritis Care Res (Hoboken). 2016;68(12): 1849–1858. pmid:27015439
- 24. Paixão ES, Rodrigues LC, Costa MDCN, Itaparica M, Barreto F, Gerardin P, et al. Chikungunya chronic disease: a systematic review and meta-analysis. Trans R Soc Trop Med Hyg. 2018;112(7): 301–316. pmid:30007303
- 25. Sengupta S, Bhattacharya N, Tripathi A. Increased CRP, anti-CCP antibody, IL-2R, COMP levels in prognosis of post-chikungunya chronic arthritis and protective role of their specific genotypes against arthritic manifestation. Virus Res. 2022;323: 198998. pmid:36356677
- 26. Dobbs JE, Tritsch SR, Encinales L, Cadena A, Suchowiecki K, Simon G, et al. Regulatory T-cells and GARP expression are decreased in exercise-associated chikungunya viral arthritis flares. Front Immunol. 2022;13: 1007106. pmid:36275717
- 27. Ranzolin A, Marques CDL, da Rocha Junior LF, Duarte ALBP, de Lima HD, de Almeida Martins LM, et al. Treatment with biological therapy is associated with faster recovery and lower frequency of treatment switch among rheumatic patients with chikungunya fever. Adv Rheumatol. 2022;62(1): 44. pmid:36376923
- 28. Frickmann H, Herchenröder O. Chikungunya virus infections in military deployments in tropical settings—a narrative minireview. Viruses. 2019;11(6): 550. pmid:31197085
- 29. Writer JV, Hurt L. Chikungunya infection in DoD healthcare beneficiaries following the 2013 introduction of the virus into the Western Hemisphere, 1 January 2014 to 28 February 2015. MSMR. 2015;22(10): 2–6. pmid:26505074
- 30. O’Donnell FL, Stahlman S, Fan M. Surveillance for vector-borne diseases among active and reserve component service members, U.S. Armed Forces, 2010–2016. MSMR. 2018;25(2): 8–15. pmid:29485891
- 31. Wellington T, Fraser JA, Kuo HC, Hickey PW, Lindholm DA. The burden of arboviral infections in the Military Health System 2012–2019. Am J Trop Med Hyg. 2023;108(5): 1007–1013. pmid:37037439
- 32.
Pollett S, Lanteri C, Forshey B, Trefry S, Winkelmann E, Nasar F, et al. Serosurveillance of chikungunya infections among U.S. military personnel deploying in the Americas, 2013–2020. ASTMH 71st Annual Meeting; October 30 to November 3, 2022; Seattle, Washington: American Society of Tropical Medicine and Hygiene. Available from: https://www.astmh.org/getmedia/65cc0d8d-1208-4d9a-9f77-734d40de4c02/ASTMH-2022-Annual-Meeting-Abstract-Book.pdf
- 33. Pollett S, Kuklis CH, Barvir DA, Jarman RG, Romaine RM, Forshey BM, et al. The seroepidemiology of dengue in a US military population based in Puerto Rico during the early phase of the Zika pandemic. PLoS Negl Trop Dis. 2022;16(1): e0009986. pmid:35061659
- 34. Hesse EM, Martinez LJ, Jarman RG, Lyons AG, Eckels KH, De La Barrera RA, et al. Dengue virus exposures among deployed U.S. military personnel. Am J Trop Med Hyg. 2017;96(5): 1222–1226. pmid:28193746
- 35. Sharp TM, Roth NM, Torres J, Ryff KR, Pérez Rodríguez NM, Mercado C, et al. Chikungunya cases identified through passive surveillance and household investigations—Puerto Rico, May 5-August 12, 2014. MMWR Morb Mortal Wkly Rep. 2014;63(48): 1121–1128. pmid:25474032
- 36. Peixoto VGMNP Azevedo JP, Luz KG Almondes KM. Cognitive dysfunction of chikungunya virus infection in older adults. Front Psychiatry. 2022;13: 823218. pmid:35449568
- 37. Doran C, Elsinga J, Fokkema A, Berenschot K, Gerstenbluth I, Duits A, et al. Long-term chikungunya sequelae and quality of life 2.5 years post-acute disease in a prospective cohort in Curacao. PLoS Negl Trop Dis. 2022;16(3): e0010142. pmid:35231033