Abstract
Background
Foreign-born persons make up approximately 5% of the United States military active duty service members. Studies in the general population show that travelers visiting friends and relatives have an increased risk of malaria acquisition. We hypothesized a higher incidence of malaria within the Military Health System (MHS) for those with a familial connection to malaria-endemic countries.
Methods
We performed a retrospective cohort study of all service members and their family members enrolled in the MHS between October 2012 and September 2018. Participants were allocated into 2 groups according to the service member's country of birth: malaria-endemic country or nonendemic country. Malaria cases were identified by International Classification of Diseases code and annual incidence rates were calculated based on service member's birth world region. Incidence rate ratios (IRRs) compared the 2 groups.
Results
Two hundred eighty-one cases of malaria were identified during the 6-year study period. The malaria-endemic group (n = 67) had 5 times the risk of malaria than the nonendemic group (n = 214) (IRR, 5.2 [95% confidence interval, 2.4–10.4]). Incidence remained higher for the malaria-endemic group even when stratified by service member and family member status. Those connected to the sub-Saharan Africa region had an average annual incidence rate of 42 cases per 100 000 persons, accounting for 86.6% of all malaria-endemic cases. Only 48% of all cases sought pretravel medical counseling.
Conclusions
There was a >5 times higher incidence of malaria in the malaria-endemic group, highlighting their increased incidence of travel-related infectious diseases despite universal health insurance coverage and access to pretravel medical care.
Keywords: foreign-born, malaria, Military Health System
Service members born in malaria-endemic countries and their families have a higher risk of malaria than those born in non-malaria-endemic countries. We highlight the need for individualized risk assessments and interventions to increase prevention services utilized by groups at increased risk.
Foreign-born persons make up approximately 5% of active duty service members in the United States (US) military [1]. These foreign-born service members and their families are a unique population in the US Military Health System (MHS) due to the potential for infectious exposures when visiting their country of birth.
In 2018, approximately 77% of imported cases of malaria in the US were associated with visiting friends and relatives (VFR) travel [2]. VFR travelers a have higher incidence of travel-related infectious diseases with higher morbidity than non-VFR travelers [3, 4]. In a prior study looking solely at US military active duty service members, 74.2% of malaria cases in the US Navy and Marine Corps were acquired from personal travel by foreign-born service members, of whom 95.5% were born in sub-Saharan Africa and had traveled to Africa [5].
The burden of these travel-related infectious diseases in the VFR population has not been previously quantified for military families. The Deployment and Travel Medicine Knowledge, Attitudes, Practices, and Outcomes Study (KAPOS) evaluates health outcomes associated with travel and deployments within the MHS. Building upon KAPOS, this study aims to quantify malaria incidence in military personnel and their families to assess if there is an association with the service member's country of birth, hypothesizing a higher incidence in those from malaria-endemic countries, particularly sub-Saharan Africa.
METHODS
Study Design
A retrospective cohort study was conducted using the MHS Data Repository (MDR), a centralized database of clinical and administrative data from the electronic medical records of 9.6 million TRICARE insurance beneficiaries seeking care at military treatment facilities (also known as direct care) worldwide including deployed locations and at US civilian clinics and hospitals (known as purchased care) [6]. Only active duty service members and their family members who were eligible for care during the 6-year study period (October 2012 to September 2018) were included in our study population.
Active duty service members (hereafter referred to simply as service members) self-report their country of birth upon accession into the military; these data were obtained from the Defense Manpower Data Center (DMDC) and linked to MDR data. The study population was then divided into 2 groups based on the service member's country of birth. Service members who were both foreign-born and with potential malaria exposure in their country of birth (based on the Centers for Disease Control and Prevention Yellow Book) were classified into the malaria-endemic group [7]. Service members born in the US or who were foreign-born in a non-malaria-endemic country were classified into the nonendemic group. Because country of birth data were not available for family members (typically spouses and children), they were linked to the service member identification number and included in the same respective group as their service member. Malaria-endemic countries were categorized into world regions as defined by the World Bank [8]. The annual total population eligible for care served as the denominator for annual incidence rates, divided for each group and world region accordingly.
The 2019 Armed Forces Health Surveillance Division (AFHSD) case definitions and incidence rules for surveillance guided our case definition designed to capture true cases of malaria [9, 10]. Malaria-specific cases were identified by 9th and 10th revision International Classification of Diseases (ICD) codes from inpatient and outpatient encounters (Figure 1). A single inpatient encounter required the ICD code in the primary or secondary location for inclusion. Outpatient-only cases required 2 outpatient encounters within 30 days of each other with the ICD code in the primary or secondary location to be included. Cases with both inpatient and outpatient encounters were classified as inpatient.
Figure 1.
Case inclusion/exclusion flowchart. Abbreviation: ICD, International Classification of Diseases.
Unless accompanied by a positive malaria-specific laboratory test, those with only a single outpatient ICD code were excluded, with the rationale being misclassification bias and not true cases. This approach was validated in recent studies of the AFHSD case definitions and the use of laboratory results to validate cases with single outpatient codes for malaria [10, 11]. Laboratory results were only available from those treated in military treatment direct-care facilities.
The diagnosis of malaria was treated as a binomial variable. All malaria-specific ICD codes were classified as “malaria.” Since malaria is curable but can recur with subsequent reinfection, we allowed participants to be included more than once during our study period. In accordance with the AFHSD case definition, counts were limited to one episode per 365 days defined by the first ICD-coded encounter date.
Demographics for malaria cases were ascertained from MDR and included age, sex, marital status, beneficiary status (service member or family member), military branch of service, and ethnicity. Of note, ethnicity is not well-populated for family members; therefore, we included an unknown category for this variable. We also assessed for pretravel healthcare prior to the malaria diagnosis by querying the MDR for at least one travel-related medication and/or travel-related vaccination administered within 365 days before the diagnosis date; details on these are described in prior KAPOS studies [12, 13].
Due to occupational risk with overseas deployments to malaria-endemic regions, deployment data were obtained from the DMDC for the service members within our cohort. This included the location and dates of deployment. Diagnosis date was compared to the deployment timeframe window and considered related to deployment if diagnosis was within 365 days before or after the deployment window. We also performed additional data extraction from the MDR's Theater Medical Data Store (TMDS) to identify cases that were diagnosed and/or treated “in theater” at deployed military medical facilities in overseas locations using the same case definition criteria as previously described. These data included the military treatment facility description, which was used to determine its geographic location.
Statistical Analysis
Descriptive statistics were summarized by categorical variables with frequency and percentages and compared using χ2 test or Fisher exact test as appropriate. Statistical differences were considered significant if P < .05. The annual incidence rate (IR) of malaria (per 100 000 person-years) was calculated for each fiscal year and then averaged for the 6-year study period. The average annual IR was calculated for the total study population, the nonendemic group, the malaria-endemic group, and each world region within the malaria-endemic group, additionally subdivided by service members and family members. The average annual IRs were used to calculate the incidence rate ratio (IRR) with 95% confidence intervals (CIs) to compare groups. All statistical analysis was performed using STATA 17.0 software (StataCorp, College Station, Texas, USA).
RESULTS
A total of 281 cases of malaria met inclusion criteria during the study period, with 67 cases categorized in the malaria-endemic group and 214 in the nonendemic group (Figure 1).
The malaria case burden is separated by risk group and demographics in Table 1. The majority of cases occurred in service members, who were predominately male. The malaria-endemic group had a higher proportion of family members and was more likely to identify as Black non-Hispanic, consistent with the high rate of service members reporting countries of birth in Africa.
Table 1.
Malaria Case Burden by Demographic Category
| Characteristic | Nonendemic | Malaria-Endemic | Total | |||
|---|---|---|---|---|---|---|
| No. | % | No. | % | No. | % | |
| No. of cases | 214 | 76.2 | 67 | 23.8 | 281 | 100 |
| Age group | ||||||
| <5 y | 9 | 4.2 | 2 | 3 | 11 | 3.9 |
| 5–17 y | 4 | 1.9 | 5 | 7.5 | 9 | 3.2 |
| ≥18 y | 201 | 93.9 | 60 | 89.6 | 261 | 92.9 |
| Sex | ||||||
| Female | 46 | 21.5 | 20 | 29.9 | 66 | 23.5 |
| Male | 168 | 78.5 | 47 | 70.1 | 215 | 76.5 |
| Marital statusa | ||||||
| Single | 96 | 44.9 | 19 | 28.4 | 115 | 40.9 |
| Married | 118 | 55.1 | 48 | 71.6 | 166 | 59.1 |
| Beneficiary statusa | ||||||
| Service member | 172 | 80.4 | 41 | 61.2 | 213 | 75.8 |
| Family member | 42 | 19.6 | 26 | 38.8 | 68 | 24.2 |
| Branch of military servicea | ||||||
| Air Force | 37 | 17.3 | 8 | 11.9 | 45 | 16 |
| Army | 131 | 61.2 | 44 | 65.7 | 175 | 62.3 |
| Coast Guard | 6 | 2.8 | 0 | 0 | 6 | 2.1 |
| Marine Corps | 19 | 8.9 | 0 | 0 | 19 | 6.8 |
| Navy | 18 | 8.4 | 14 | 20.9 | 32 | 11.4 |
| Public Health Service | 3 | 1.4 | 1 | 1.5 | 4 | 1.4 |
| Ethnicitya | ||||||
| American Indian or Alaska Native | 1 | 0.5 | 0 | 0 | 1 | 0.4 |
| Asian or Pacific Islander | 6 | 2.8 | 2 | 3 | 8 | 2.9 |
| Black, not Hispanic | 25 | 11.7 | 41 | 61.2 | 66 | 23.5 |
| White, not Hispanic | 124 | 57.9 | 2 | 3 | 126 | 44.8 |
| Hispanic | 22 | 10.3 | 1 | 1.5 | 23 | 8.2 |
| Unknown | 35 | 16.4 | 21 | 31.3 | 56 | 19.9 |
aSignifies P < .05 using the χ2 test or Fisher exact test to compare nonendemic cases and malaria-endemic cases within each demographic category.
During our study period, the overall malaria average annual IR was 2.3 cases per 100 000 person-years (Table 2). The malaria-endemic group had 5 times the risk of malaria compared with the nonendemic group. The risk remained higher for the malaria-endemic group when stratified by service member and family member status (Table 2), with malaria-endemic family members having nearly 16 times higher risk than nonendemic family members. When compared only within the malaria-endemic group, service members had nearly 3 times higher risk of malaria as compared to their own family members, but this was not significant (IRR, 2.9 [95% CI, .7–13.6]; P = .09).
Table 2.
Average Annual Incidence Rate (Cases per 100 000 Person-years)
| Malaria Group | Total | Service Members | Family Members |
|---|---|---|---|
| Total | 2.3 | 2.3 | 0.6 |
| Nonendemic group | 1.8 | 1.9 | 0.4 |
| Malaria-endemic group | 9.7 | 15.9 | 6 |
| Latin America & Caribbean | 4.7 | 5.3 | 4.4 |
| Europe & Central Asia | 0 | 0 | 0 |
| Middle East & North Africa | 0 | 0 | 0 |
| Sub-Saharan Africa | 41.9 | 74.1 | 23.7 |
| South Asia | 3.3 | 0 | 6.1 |
| East Asia & Pacific | 0.7 | 1.3 | 0.4 |
| IRR (95% CI)a | 5.2 (2.4–10.4) | 8.5 (3.1–19.8) | 15.8 (3.4–62.1) |
Abbreviations: CI, confidence interval; IRR, incidence rate ratio.
aMalaria-endemic vs nonendemic.
Over 86% of malaria-endemic group cases had a familial connection (either directly or through an immediate family member) to sub-Saharan Africa while sub-Saharan Africa only accounted for 20% of the broader malaria-endemic group population. Sub-Saharan Africa had the highest malaria average annual IR of 42 cases per 100 000 person-years, which is >4 times that of the malaria-endemic group rate and 18 times higher than the total study population (Table 2). The top 3 countries of birth (within the malaria-endemic group) with the highest percentage of malaria cases were all located in sub-Saharan Africa: Nigeria (25.4%), Ghana (11.9%), and Kenya (10.5%). East Asia and the Pacific accounted for only 4.5% of the malaria-endemic group cases despite being the largest proportion (60.1%) of the group's population. There were no cases of malaria among those born in the Middle East and North Africa region; note that only 4 of the 21 countries within this region have areas endemic to malaria (Djibouti, Iran, Saudi Arabia, and Yemen).
Two-thirds of all cases were managed at least partially in the inpatient setting, with no difference between the groups (Table 3). The type of care did not differ between direct care, purchased care, or both. One hundred thirty-five cases (48%) had evidence of a pretravel medical visit, of which 89 (65.9%) were prescribed malaria chemoprophylaxis, and there was no difference between the groups. Nearly half of the cases did not have a Plasmodium species specified based on ICD codes. Approximately one-third of all cases had an ICD code pertaining to P falciparum, with a significantly higher proportion occurring in the malaria-endemic group (65.7% vs 21.5%, P < .01; Table 3). Only 37.7% of all cases had associated malaria-specific laboratory testing available for review, but this may be falsely low as laboratory testing data were only available from those treated in direct-care facilities. The malaria-endemic group had significantly more cases with laboratory testing performed (52.2% vs 33.2%, P < .01), but there was no difference in the number of tests performed. Similar to the ICD codes, P falciparum was the species most frequently identified; while the proportion was higher for the malaria-endemic group, it was not statistically significant (48.6% vs 19.7%, P = .07).
Table 3.
Clinical Data
| Characteristic | Nonendemic | Malaria-Endemic | Total | |||
|---|---|---|---|---|---|---|
| No. | % | No. | % | No. | % | |
| ICD code setting | ||||||
| Inpatient | 131 | 61.2 | 45 | 67.2 | 176 | 62.6 |
| Outpatient-only | 83 | 38.8 | 22 | 32.8 | 105 | 37.4 |
| Type of care | ||||||
| Purchased care (civilian) only | 87 | 40.6 | 29 | 43.3 | 116 | 41.3 |
| Direct care (military) only | 117 | 54.7 | 34 | 50.8 | 151 | 53.7 |
| Combination purchased + direct care | 10 | 4.7 | 4 | 5.9 | 14 | 5.0 |
| Evidence of pretravel visit | ||||||
| No | 109 | 50.9 | 37 | 55.2 | 146 | 53.0 |
| Yes | 105 | 49.1 | 30 | 44.8 | 135 | 48.0 |
| Pretravel visit resulting in malaria prophylaxis prescription (n = 135) | ||||||
| No | 36 | 34.3 | 10 | 33.3 | 46 | 34.1 |
| Yes | 69 | 65.7 | 20 | 66.7 | 89 | 65.9 |
| Malaria species based on ICD codea | ||||||
| Plasmodium falciparum | 46 | 21.5 | 44 | 65.7 | 90 | 32.0 |
| Plasmodium malariae | 0 | 0 | 0 | 0 | 0 | 0 |
| Plasmodium ovale | 2 | 0.9 | 0 | 0 | 2 | 0.7 |
| Plasmodium vivax | 50 | 23.4 | 0 | 0 | 50 | 17.8 |
| Mixed (either “mixed” or ≥2 ICD codes with different species) | 10 | 4.7 | 0 | 0 | 10 | 3.6 |
| Unspecified | 106 | 49.5 | 23 | 34.3 | 128 | 45.9 |
Abbreviation: ICD, International Classification of Diseases.
aSignifies P < .05 using the χ2 test or Fisher exact test to compare nonendemic cases and malaria-endemic cases within each clinical data category.
There were 31 service members diagnosed with malaria within the context of deployments (Table 4). Triangulation of data across the DMDC and TMDS was an important aspect of case ascertainment. Initially, only 2 cases were identified using the DMDC deployment data and these were to unspecified locations. Assessing for in-theater medical care revealed an additional 29 cases, of which 8 were already in our cohort of fixed-facility medical care but did not have identified deployment location data. Thus 93.6% of deployment-related cases were diagnosed while in the theater of operations overseas. The majority of these cases served in the Army, with Afghanistan accounting for the largest proportion (69%) of in-theater diagnoses. Those individuals in the malaria-endemic group had a smaller proportion of deployment-related cases as compared to the nonendemic group (4.9% vs 16.9%, respectively, P = .05; Table 4).
Table 4.
Deployment-Related Malaria Cases in Service Members
| Characteristic | Nonendemic | Malaria-Endemic | Total | |||
|---|---|---|---|---|---|---|
| No. | % | No. | % | No. | % | |
| Malaria diagnosis related to deployment window (n = 213) (P = .05) | ||||||
| No | 143 | 83.1 | 39 | 95.1 | 182 | 85.5 |
| Yes | 29 | 16.9 | 2 | 4.9 | 31 | 14.6 |
| Diagnosis occurred in-theater (n = 31)a | ||||||
| No | 1 | 3.5 | 1 | 50 | 2 | 6.5 |
| Yes | 28 | 96.6 | 1 | 50 | 29 | 93.6 |
| Branch of service of deployed service member (n = 31) | ||||||
| Air Force | 1 | 3.5 | 0 | 0 | 1 | 3.2 |
| Army | 25 | 86.21 | 1 | 50 | 26 | 83.87 |
| Coast Guard | 2 | 6.9 | 0 | 0 | 2 | 6.5 |
| Marine Corps | 0 | 0 | 0 | 0 | 0 | 0 |
| Navy | 1 | 3.5 | 1 | 50 | 2 | 6.5 |
| Public Health Service | 0 | 0 | 0 | 0 | 0 | 0 |
| Location of military treatment facility in-theater (n = 29) | ||||||
| Afghanistan | 19 | 67.9 | 1 | 100 | 20 | 69.0 |
| Djibouti | 2 | 7.1 | 0 | 0 | 2 | 6.9 |
| Germany (medical evacuation | 1 | 3.6 | 0 | 0 | 1 | 3.5 |
| Niger | 2 | 7.1 | 0 | 0 | 2 | 6.9 |
| Qatar | 1 | 3.6 | 0 | 0 | 1 | 3.5 |
| Unknown | 3 | 10.7 | 0 | 0 | 3 | 10.3 |
aSignifies P < .05 using the χ2 test or Fisher exact test to compare nonendemic cases and malaria-endemic cases within each deployment-related category.
DISCUSSION
Among service members and their families, the incidence of malaria was 5 times higher in the malaria-endemic group compared to the nonendemic group, indicating a strong effect for the presence of malaria in a service member's country of birth. The highest proportion of malaria cases within the malaria-endemic group was associated with service member birth in sub-Saharan Africa, which also had the overall highest malaria IR in our study. Similarly, Wertheimer et al found in a 2002–2010 study that US military service members born in one of 7 West African countries had a 44 times higher rate of malaria infection as compared to those born in the US [14]. Our study builds upon and extends the knowledge gained from Wertheimer et al by including family members, highlighting the increased risk for malaria in this subpopulation of military families.
Our study design did not include individual chart review to ascertain purpose and location of travel, so we can only make limited inferences, but we suspect many of the malaria cases were acquired on personal travel for both the service member and family members, particularly VFR travel among the foreign-born group. Wertheimer et al estimated that up to 90% of malaria cases in African-born service members were acquired from visiting their country of birth [14]. Only 14.6% of service members had a diagnosis associated with a known deployment.
Within the malaria-endemic group, service members had an almost 3 times higher rate of malaria as compared to their family members. In our clinical experience, foreign-born parents will bring their US-born children for pretravel medical care prior to VFR travel to a malaria-endemic country but the parent may not seek care themselves. This finding is supported by a GeoSentinel Surveillance Network study that found only 16% of immigrant VFRs, analogous to our malaria-endemic group service members, sought pretravel medical counseling as compared to 47% of traveler VFRs, second-generation immigrant travelers similar to our malaria-endemic group family members [4]. As such, immigrant VFRs had more than twice the odds of malaria after travel to sub-Saharan Africa as compared to traveler VFRs [4]. It highlights that the provision of “family travel visits” may be a best practice, and that, at a minimum, providers of pediatric travel medicine services should always inquire if the adults have also obtained pretravel healthcare. Although family clusters of malaria cases may be observed due to travel together, this was not observed in our dataset.
While the overall incidence of malaria in family members was low, family members in the malaria-endemic group had a 15 times higher rate of malaria as compared to the nonendemic group, almost twice the rate observed in service members for the same comparison. The selection process to be admitted into the US military includes rigorous medical screenings, resulting in a population that is healthier than civilian counterparts of similar demographics [15]. By including family members in our study, we have minimized the “healthy warrior effect” selection bias by broadening the potential for comorbid conditions within the study population that may contribute to disease burden. This provides an important new epidemiological context that is relevant to non-military-associated immigrant communities in the US and may help influence assessments of disease burden and prevention efforts in similar groups likely to engage in VFR travel in the future.
It is unclear from our data why this increased malaria incidence occurred in the malaria-endemic group considering that the Department of Defense provides no-cost or low-cost universal health insurance to the study population, effectively eliminating the healthcare access disparities seen in other populations. As such, further investigation is needed to determine the root cause(s) and to provide insight and better target future malaria prevention efforts. We plan to perform individual chart reviews for these malaria cases identified within the MHS to elicit risk factors for malaria, probe for documented birth location of family members, and assess if pretravel medical counseling followed the force health protection guidelines for the service members.
One of our study's strengths is its large size, which includes a socioeconomically diverse population with universal healthcare coverage; when used as the denominator for incidence, it is all-encompassing. In addition to ICD codes, malaria-specific laboratory data, and encounter dates, we obtained individual-level prescription medication and immunization information from the MDR to assess for pretravel healthcare. In requiring 2 close-proximity outpatient ICD codes, we attempted to decrease the risk of including false cases when an ICD code is improperly used when prescribing malaria chemoprophylaxis prior to travel, rather than for clinical malaria.
The major limitation of our study was the risk of nondifferential misclassification error of disease status as we used ICD codes to determine each case based on a case definition defined and refined by the AFHSD [9–11]. Applying a correction factor calculated from cases and controls can significantly reduce misclassification bias in epidemiologic studies that utilize electronic medical records for outcome variables [16]. Validation of the AFHSD case definition included a review of individual electronic medical records from a random subset of cases and noncases. The calculated correction factor for misclassification bias was applied to estimate the true number of malaria cases, which aligned with the number of cases identified by the case definition [11]. Future analyses could further decrease this error by applying validation statistics of each ICD code to the dataset. We used the ICD code details to classify the cases by malaria species but, notably, >70% of cases were associated with a nonspecific malaria ICD code. This reflects the lack of detailed coding by the provider and does not indicate a deficiency in species detection on laboratory testing. As our study was based on billing data, we were unable to confirm if the ICD code species corresponded correctly with laboratory data for the purchased care cases.
It is possible that the ascertainment of malaria cases may be incomplete. Some malaria cases may have been treated at purchased care locations, particularly outpatient while traveling abroad; these would not be captured in the MDR unless a claim was sent back to TRICARE for payment by either the facility or for reimbursement of the beneficiary. The individual family member's birth country is unknown; we applied the service member's birth country status to all family members attributing VFR travel risks for malaria acquisition to the family unit. It is also possible that a service member from a non-malaria-endemic country is married to a person born in a malaria-endemic country, thus falsely increasing the denominator and cases in the nonendemic group at the expense of the malaria-endemic group.
Further studies are needed to distinguish the impact of foreign birth within our military family population and to assess if there are similar associations with other infectious diseases. We intend to administer surveys and focus groups of foreign-born service members to assess personal and family travel patterns, health-seeking behaviors, and health outcomes. In particular, we caution against a prejudgment that VFR travelers fail to appreciate the risk of malaria while traveling and would expand underlying considerations to include the possibility that they may lack confidence in the malaria-related knowledge or abilities of US-based physicians.
CONCLUSIONS
This study found a significantly higher incidence of malaria among groups of service members and their families in which the service member was born in a malaria-endemic country. Additional studies are needed to determine why this group within MHS has a higher incidence of malaria in spite of access to no-cost or low-cost pretravel healthcare and policies for pretravel medical visits for service members. Specifically, there is a need to assess interventions that could reduce further the travel-related disease burden across the MHS.
Notes
Acknowledgments. The first author would like to acknowledge several people who significantly contributed to the successful completion of this project. Dr Ann Scher, Dr Jennifer Rusiecki, and Ms Sorana Raiciulescu provided insight into epidemiologic design. Dr David Stagliano was the first author's fellowship program director and Dr Darrell Singer and Dr Bernard Okech were the first author's MPH advisors, all of whom provided support throughout the project.
Author contributions. A. M. H.: Conceptualization, methodology, investigation, data curation, formal analysis, writing—original draft & revisions. D. L.: Conceptualization, methodology, data extraction. M. G.: Conceptualization, data extraction. X. C.: Methodology, data extraction. P. W. H.: Funding acquisition, conceptualization, methodology, writing—reviewing & editing, supervision.
Patient consent. This research protocol was reviewed and approved by the Uniformed Services University of the Health Sciences Institutional Review Board. The investigators have adhered to the policies for protection of human subjects as prescribed in 45 Code of Federal Regulations 46. This study does not include factors necessitating patient consent.
Disclaimer. The views expressed are those of the authors and do not reflect the official policy of the Department of the Army, Department of the Navy, the Department of the Air Force, the Department of Defense or the US government, or the Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc. This work was prepared by a military employee of the US government as part of the individual's official duties and therefore is in the public domain and does not possess copyright protection (public domain information may be freely distributed and copied; however, as a courtesy it is requested that the Uniformed Services University and the authors be given an appropriate acknowledgment).
Financial support. This work (IDCRP-097) was supported by the Infectious Disease Clinical Research Program, a Department of Defense program executed by the Uniformed Services University of the Health Sciences through a cooperative agreement with The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc. This project has been supported with federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, under Interagency Agreement Y1-Al-5072 and from the Defense Health Program, US Department of Defense, under award HU0001190002. Grant funding was awarded to P. W. H.
Contributor Information
Alison M Helfrich, Department of Pediatrics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA.
Dan Lu, Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA; The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, Maryland, USA.
Melissa Grance, Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA; The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, Maryland, USA.
Xiuping Chu, Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA; The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, Maryland, USA.
Patrick W Hickey, Department of Pediatrics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA.
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