• View in gallery

    Rates of upper respiratory illness (URI) by cohort in camp A (blue boxes) and camp B (orange boxes). The area of boxes is proportional to the size of each cohort. Gray lines indicate 95% confidence intervals. No URI cases were detected in camp A during the May 2014 training period.

  • View in gallery

    Pathogens detected in upper respiratory illness (URI) cases by camp, training cohort, and day of onset relative to the start of follow-up. Size and color of circles indicate number of URI cases in which a given pathogen was detected.

  • View in gallery

    Distribution of antibody titers as measured by hemagglutinin inhibition assay at baseline (y axis) and follow-up (x axis). The color scale indicates the proportion of sample pairs in each titer combination. Gray squares denote a ≥ 4-fold increase in antibody titer at follow-up. Row totals indicate the probability distribution of baseline titers.

  • 1.

    Korzeniewski K, Nitsch-Osuch A, Konior M, Lass A, 2015. Respiratory tract infections in the military environment. Respir Physiol Neurobiol 209: 7680.

    • Search Google Scholar
    • Export Citation
  • 2.

    Korzeniewski K, Nitsch-Osuch A, Chciałowski A, Korsak J, 2013. Environmental factors, immune changes and respiratory diseases in troops during military activities. Respir Physiol Neurobiol 187: 118122.

    • Search Google Scholar
    • Export Citation
  • 3.

    Chen MIC et al. 2010. 2009 influenza A(H1N1) seroconversion rates and risk factors among distinct adult cohorts in Singapore. JAMA 303: 13831391.

    • Search Google Scholar
    • Export Citation
  • 4.

    Cheng J et al. 2016. Epidemiology and transmission characteristics of human adenovirus type 7 caused acute respiratory disease outbreak in military trainees in east China. Am J Transl Res 8: 23312342.

    • Search Google Scholar
    • Export Citation
  • 5.

    Yoo H et al. 2017. Febrile respiratory illness associated with human adenovirus type 55 in South Korea military, 2014–2016. Emerg Infect Dis 23: 10161020.

    • Search Google Scholar
    • Export Citation
  • 6.

    Yu P, Ma C, Nawaz M, Han L, Zhang J, Du Q, Zhang L, Feng Q, Wang J, Xu J, 2013. Outbreak of acute respiratory disease caused by human adenovirus type 7 in a military training camp in Shaanxi, China. Microbiol Immunol 57: 553560.

    • Search Google Scholar
    • Export Citation
  • 7.

    Halhal B, Glick Y, Galor I, Ran A, Bacon DJ, Glassberg E, 2017. Pertussis outbreak among soldiers during basic training: the need for updated protocols. Mil Med 182: 355359.

    • Search Google Scholar
    • Export Citation
  • 8.

    Clemmons NS, McCormic ZD, Gaydos JC, Hawksworth AW, Jordan NN, 2017. Acute respiratory disease in US army trainees 3 years after reintroduction of adenovirus vaccine. Emerg Infect Dis 23: 9598.

    • Search Google Scholar
    • Export Citation
  • 9.

    Gray J, Coupland LJ, 2014. The increasing application of multiplex nucleic acid detection tests to the diagnosis of syndromic infections. Epidemiol Infect 142: 111.

    • Search Google Scholar
    • Export Citation
  • 10.

    Reddington K, Tuite N, Barry T, O’Grady J, Zumla A, 2013. Advances in multiparametric molecular diagnostics technologies for respiratory tract infections. Curr Opin Pulm Med 19: 298304.

    • Search Google Scholar
    • Export Citation
  • 11.

    Levy JW et al. 2015. Elevated transmission of upper respiratory illness among new recruits in military barracks in Thailand. Influenza Other Respir Viruses 9: 308314.

    • Search Google Scholar
    • Export Citation
  • 12.

    World Health Organization, 2009. CDC Protocol of Realtime RTPCR for Influenza A(H1N1). Available at: http://www.who.int/csr/resources/publications/swineflu/CDCRealtimeRTPCR_SwineH1Assay-2009_20090430.pdf. Accessed March 14, 2018.

  • 13.

    Centers for Disease Control and Prevention, 2007. CDC Realtime RT-PCR (rRTPCR) Protocol for Detection and Characterization of Influenza. Atlanta, GA: CDC.

  • 14.

    Salez N, Vabret A, Leruez-Ville M, Andreoletti L, Carrat F, Renois F, de Lamballerie X, 2015. Evaluation of four commercial multiplex molecular tests for the diagnosis of acute respiratory infections. PLoS One 10: e0130378.

    • Search Google Scholar
    • Export Citation
  • 15.

    Sakthivel SK, Whitaker B, Lu X, Oliveira DBL, Stockman LJ, Kamili S, Oberste MS, Erdman DD, 2012. Comparison of fast-track diagnostics respiratory pathogens multiplex real-time RT-PCR assay with in-house singleplex assays for comprehensive detection of human respiratory viruses. J Virol Methods 185: 259266.

    • Search Google Scholar
    • Export Citation
  • 16.

    Millar EV, Schlett CD, Law NN, Chen W-J, D’Onofrio MJ, Bennett JW, Tribble DR, Ellis MW, 2016. Reduction in acute respiratory infection among military trainees: secondary effects of a hygiene-based cluster-randomized trial for skin and soft-tissue infection prevention. Infect Control Hosp Epidemiol 37: 11181120.

    • Search Google Scholar
    • Export Citation
  • 17.

    Phillips CJ, Woolpert T, Sevick C, Faix D, Blair PJ, Crum-Cianflone NF, 2013. Comparison of the effectiveness of trivalent inactivated influenza vaccine and live, attenuated influenza vaccine in preventing influenza-like illness among US military service members, 2006–2009. Clin Infect Dis 56: 1119.

    • Search Google Scholar
    • Export Citation
  • 18.

    Ryan MA, Christian RS, Wohlrabe J, 2001. Handwashing and respiratory illness among young adults in military training. Am J Prev Med 21: 7983.

    • Search Google Scholar
    • Export Citation
  • 19.

    Prachayangprecha S, Vichaiwattana P, Korkong S, Felber JA, Poovorawan Y, 2015. Influenza activity in Thailand and occurrence in different climates. Springerplus 4: 356.

    • Search Google Scholar
    • Export Citation
  • 20.

    Hobson D, Curry RL, Beare AS, Ward-Gardner A, 1972. The role of serum haemagglutination-inhibiting antibody in protection against challenge infection with influenza A2 and B viruses. J Hyg (Lond) 70: 767777.

    • Search Google Scholar
    • Export Citation
  • 21.

    Potter CW, Oxford JS, 1979. Determinants of immunity to influenza infection in man. Br Med Bull 35: 6975.

  • 22.

    Ng S, Fang VJ, Ip DKM, Chan K-H, Leung GM, Peiris JSM, Cowling BJ, 2013. Estimation of the association between antibody titers and protection against confirmed influenza virus infection in children. J Infect Dis 208: 13201324.

    • Search Google Scholar
    • Export Citation
  • 23.

    Coudeville L, Bailleux F, Riche B, Megas F, Andre P, Ecochard R, 2010. Relationship between haemagglutination-inhibiting antibody titres and clinical protection against influenza: development and application of a bayesian random-effects model. BMC Med Res Methodol 10: 18.

    • Search Google Scholar
    • Export Citation
  • 24.

    Agrawal A, Murphy TF, 2011. Haemophilus influenzae infections in the H. influenzae type b conjugate vaccine era. J Clin Microbiol 49: 37283732.

    • Search Google Scholar
    • Export Citation
 
 
 

 

 
 
 

 

 

 

 

 

 

Epidemiology and Transmission of Respiratory Infections in Thai Army Recruits: A Prospective Cohort Study

View More View Less
  • 1 Saw Swee Hock School of Public Health, National University of Singapore and National University Health Systems, Singapore, Singapore;
  • | 2 London School of Hygiene & Tropical Medicine, London, United Kingdom;
  • | 3 University of Minnesota, Minneapolis, Minnesota;
  • | 4 Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand;
  • | 5 Phramongkutklao College of Medicine, Bangkok, Thailand;
  • | 6 US Army Institute of Surgical Research, San Antonio, Texas;
  • | 7 Phramongkutklao Hospital, Bangkok, Thailand

Military recruits are at high risk of respiratory infections. However, limited data exist on military populations in tropical settings, where the epidemiology of respiratory infections differs substantially from temperate settings. We enrolled recruits undertaking a 10-week military training at two Royal Thai Army barracks between May 2014 and July 2015. We used a multiplex respiratory panel to analyze nose and throat swabs collected at the start and end of the training period, and from participants experiencing respiratory symptoms during follow-up. Paired sera were tested for influenza seroconversion using a hemagglutinin inhibition assay. Overall rates of upper respiratory illness and influenza-like illness were 3.1 and 2.0 episodes per 100 person-weeks, respectively. A pathogen was detected in 96% of samples. The most commonly detected microbes were Haemophilus influenzae type B (62.7%) or non–type B (58.2%) and rhinovirus (22.4%). At baseline, bacterial colonization was high and included H. influenzae type B (82.3%), H. influenzae non–type B (31.5%), Klebsiella pneumoniae (14.6%), Staphylococcus aureus (8.5%), and Streptococcus pneumoniae (8.5%). At the end of follow-up, colonization with H. influenzae non–type B had increased to 74.1%, and S. pneumoniae to 33.6%. In the serology subset, the rate of influenza infection was 3.4 per 100 person-months; 58% of influenza infections resulted in clinical disease. Our study provides key data on the epidemiology and transmission of respiratory pathogens in tropical settings. Our results emphasize the need for improved infection prevention and control in military environments, given the high burden of illness and potential for intense transmission of respiratory pathogens.

INTRODUCTION

Military recruits are at high risk of respiratory infections.1 The congregation of individuals from diverse geographic locations in semi-closed settings, together with high levels of close contact, provide conditions that favor the introduction and transmission of respiratory pathogens.2 Studies among military recruits have found high rates of illness and infection with respiratory viruses. A longitudinal study in Singapore found that 39.4% of military personnel had evidence of seroconversion against influenza A/H1N1 during the 2009 pandemic, compared with 13.5% of individuals in the community and 6.5% of hospital staff.3 Numerous outbreaks of respiratory infections among military recruits have been reported in the literature, including outbreaks of influenza, adenovirus,46 and pertussis.7 Resumption of vaccination against adenovirus types 4 and 7 in the U.S. military is estimated to have resulted in a 7-fold decrease in acute respiratory disease8 and a shift in the predominant adenovirus types from types 4, 3, and 7 to types 1 and 2.

The increasing availability of multiplex molecular diagnostic assays can yield data on multiple pathogens that would not routinely be detected.9,10 Studies in military populations can provide valuable information regarding the epidemiology and transmission of respiratory infections in adults because of the availability of well-defined populations that can be followed up over time. Despite this, data from tropical settings, in which the epidemiology of influenza and other respiratory infections differs substantially from temperate settings, are limited. Increased understanding of the etiology of respiratory infections in these settings is important to identify opportunities for disease control in high-risk military populations and to identify risks of pathogen emergence with potential for spread into the wider community.

We present the results of a longitudinal study of the burden and etiology of respiratory infections in Thai military recruits.

MATERIALS AND METHODS

The study setting and procedures have been previously described.11 Between May 2014 and May 2015, we enrolled participants from consecutive cohorts of recruits undertaking basic military training at two Royal Thai Army (RTA) barracks in Bangkok. Trainees entered the camps at the start of May and November each year and remained in the camps for 10 weeks. The camps consist of large, common sleeping quarters with beds arranged foot-to-foot in long rows. Trainees share meals in a common canteen and train in a large field in the center of the barracks and a number of ancillary buildings. Each camp has its own medical unit.

Individuals were eligible for enrollment if they were aged ≥ 18 years and were entering one of the two army barracks involved in the study. Suspected tuberculosis cases or individuals with immune deficiencies, such as acquired immune deficiency syndrome, leukemia, or lymphoma, were excluded. Individuals providing informed consent were enrolled in the study and a demographic and clinical questionnaire was administered. Participants were then followed up for symptoms of respiratory illness until the end of the 10-week training period. At one camp, nasal and throat swabs were obtained at the time of enrolment and at the end of the follow-up period (10 weeks later) from consenting participants. Participants experiencing respiratory symptoms were asked to consult the medical unit, where medical staff took a history, conducted a medical examination, and recorded symptoms of upper respiratory illness (URI) or influenza-like illness (ILI). Upper respiratory illness was defined as an illness with at least two of the following: 1) runny nose or sneezing; 2) nasal congestion; 3) sore throat, hoarseness, or difficulty swallowing; 4) cough; 5) swollen or tender glands in the neck; and 6) fever (oral temperature > 38°C) at the time of presentation. Influenza-like illness was defined as a respiratory illness with acute onset presenting with fever and cough or sore throat. All ILI cases also met the case definition for URI. Non-ILI cases were defined as URI cases not meeting the case definition for ILI. Additional nasal and throat swabs were requested from participants presenting with acute ILI or URI.

Laboratory investigations.

Nasal and throat swabs were placed in viral transport media and stored at −20°C until transfer to the Armed Forces Research Institute of Medical Sciences for further testing. We tested acute swabs for influenza virus using reverse transcription polymerase chain reaction (RT-PCR) following the U.S. Centers for Disease Control protocol.12,13 We also tested acute samples (from both camps) and the routine enrolment and follow-up specimens (from one camp) using a multiplex real-time PCR assay comprising 33 bacterial, viral, and fungal targets (FTD33 kit; Fast Track Diagnostics, Esch-sur-Alzette, Luxembourg). A cycle threshold value of < 33 was considered a positive result. Previous studies have shown high agreement between FTD33 and other commercial multiplex assays with specificities > 95% for most viral targets.14,15 Sensitivity for influenza A and B, and human coronaviruses is high (> 90%), but is lower and more variable for other viral targets, including human bocavirus (80–92%), rhinovirus (61–75%), respiratory syncytial virus (50–72%), and human metapneumovirus (74–100%).14,15

In a subset of recruits, we measured influenza antibody titers in paired sera taken at enrollment and at the end of follow-up using a hemagglutinin inhibition assay. Seroconversion was defined as a 4-fold rise in influenza subtype-specific antibody titers.

Statistical analysis.

Rates of illness.

Individuals were considered at risk from the date they entered the camp for a period of 10 weeks. We computed the rates of URI and ILI as the number of cases of each outcome divided by the total person-time at risk, using robust standard errors in the calculation of 95% confidence intervals (CIs) to allow for clustering of illness episodes by camp and cohort.

Disease etiology.

We determined the percentage of URI and ILI cases positive for each target pathogen, the percentage positive for more than one pathogen, and the percentage with no pathogen identified.

Influenza seroconversion.

We calculated the percentage of recruits who seroconverted, overall and by influenza subtype, based on a 4-fold rise in antibody titer between baseline and end of follow-up samples.

Bacterial colonization.

We determined the percentage of recruits with a positive identification of a bacterial pathogen at recruitment, the overall change in colonization prevalence between baseline and end of follow-up for each bacterial species, and the risk of acquisition of bacterial pathogens over the follow-up period among those initially negative.

Antibiotic use.

We calculated the percentage of URI and ILI cases that were prescribed antibiotics and investigated clinical signs and symptoms associated with antibiotic prescription using logistic regression. Among those prescribed antibiotics, we determined the fraction of cases with a likely viral etiology based on the available Fast Track multiplex PCR results.

Analyses were conducted using Stata 11 (StataCorp, College Station, TX) and R 3.2.2.

Ethical approval.

The study was approved by the Institutional Review Boards of the RTA in Bangkok, Thailand, the Walter Reed Army Institute of Research, and the London School of Hygiene & Tropical Medicine. All participants provided written informed consent.

RESULTS

Three cohorts of army recruits undertook basic military training at the two camps during the study period, in May 2014–July 2014, November 2014–January 2015, and May 2015–July 2015. In total, 933 recruits undertook training during these three periods. Of these, 867 (93%) were enrolled in the study. Of the 867 participants, five participants withdrew from the study and 44 participants recruited in November 2014 were transferred out of the camp to complete their training elsewhere. The remaining 818 (94%) completed the 10-week follow-up and were included in the analysis. All participants were male and the median age was 21 years (range: 20–29 years). Details of recruitment and follow-up completion for each cohort are given in Supplemental Figure 1.

Rates of illness.

There were a total of 248 episodes of URI and 8,063 person-weeks of follow-up, yielding an overall URI rate of 3.1 per 100 person-weeks. Upper respiratory illness rates ranged from 2.6 to 4.6 per 100 person-weeks across cohorts, with the exception of the camp A May 2014 cohort, in which no URI episodes were reported (Figure 1). There were 160 ILI episodes, giving an overall ILI rate of 2.0 per 100 person-weeks, ranging from 0 to 4.1 per 100 person-weeks across cohorts.

Figure 1.
Figure 1.

Rates of upper respiratory illness (URI) by cohort in camp A (blue boxes) and camp B (orange boxes). The area of boxes is proportional to the size of each cohort. Gray lines indicate 95% confidence intervals. No URI cases were detected in camp A during the May 2014 training period.

Citation: The American Journal of Tropical Medicine and Hygiene 99, 4; 10.4269/ajtmh.18-0219

Symptoms and time off work.

Fever was present in nearly two-thirds of URI episodes. Cough and sore throat occurred in > 90% of URI episodes, nasal congestion and headache in > 80% of episodes, and malaise and breathing difficulty in > 60% of episodes. All these symptoms were significantly more common in ILI compared with non-ILI episodes (Table 1). Influenza-like illness cases were also more likely to take time off work than non-ILI cases (57.5% versus 13.6%, P < 0.001), although the length of time taken off work was short (median 1 day). There was one hospitalization in an individual diagnosed with pneumonia who was off work for 7 days.

Table 1

Distribution of symptoms in URI and ILI cases among Royal Thai Army recruits

SymptomURI (N = 248)ILI (N = 160)Non-ILI (N = 88)P value*
Number(%)Number(%)Number(%)
Fever16064.5160100.000.0< 0.001
Cough23695.215798.17989.80.005
Sore throat23293.515697.57686.40.002
Nasal congestion20482.315496.35056.8< 0.001
Headache20984.314691.36371.6< 0.001
Malaise17169.014389.42831.8< 0.001
Breathing difficulty15662.913986.91719.3< 0.001
Muscle ache14156.913685.055.7< 0.001
Tonsillitis5522.25031.355.7< 0.001
Swollen lymph nodes5020.14326.978.0< 0.001
Paralysis4216.94025.022.3< 0.001
Chills3714.93622.511.1< 0.001
Diarrhea166.5148.822.30.058
Stiffness10.410.600.01.000
Vision or hearing loss10.410.600.01.000
Impact on daily duties:
 Stopped working10441.99257.51213.6< 0.001
 Assigned lighter duties7128.63823.83337.5
Days off work (median [IQR])0 (0–1)1 (0–1)< 0.001

ILI = influenza-like illness; URI = upper respiratory illness.

Fisher’s exact test comparing ILI and non-ILI cases.

IQR = interquartile range.

Disease etiology.

Among the 134 URI and ILI samples tested by multiplex PCR, a pathogen was detected in 128. A single pathogen was detected in 26% of samples, two pathogens in 31%, three pathogens in 26%, and four pathogens in 12%. Among URI pathogens, the most common viruses detected were rhinoviruses (22.4%), influenza B (11.9%), coronavirus 229 (5.2%), adenovirus (3.0%), and influenza A/H3 (3.0%). Other viruses accounted for < 3% of URI cases each. Of 133 samples tested for influenza by both RT-PCR and the Fast Track multiplex assay, 20 (15%) tested positive by at least one assay, and all of these were also positive by RT-PCR. Of the 20 RT-PCR positives, four were positive for influenza A/H3, of which one was also positive by the multiplex assay. Of the remaining 16 positive for influenza B by RT-PCR, 14 were also positive by the multiplex assay. There were no samples that tested positive by the multiplex assay and negative by RT-PCR.

Among the bacteria, the most commonly detected species were Haemophilus influenzae type B (62.7%), H. influenzae non–type B (58.2%), Streptococcus pneumoniae (16.4%), and Klebsiella pneumoniae (16.4%). However, these were commonly found in combination with other pathogens. When considering only samples in which a single organism was found, H. influenzae type B was found in 13.4% of samples, H. influenzae non–type B in 9.0%, and S. pneumoniae, K. pneumoniae, and Legionella pneumophila in 0.7% each. There was little evidence to suggest that etiological agents differed between ILI and non-ILI cases, with the exception of H. influenzae non–type B and coronavirus 229, which occurred more frequently in non-ILI cases, and influenza A/H3 and coronavirus HKU1, which occurred more frequently in ILI cases (Table 2).

Table 2

Distribution of respiratory pathogens in a subset of URI and ILI cases among Royal Thai Army recruits tested by Fast Track multiplex respiratory panel (FTD33)

Pathogen typeURI (N = 134)ILI (N = 48)Non-ILI (N = 86)P value*
PathogenPositive%Positive%Positive%
BacteriaHaemophilus influenzae B8462.73572.94957.00.093
H. influenzae non-B7858.21633.36272.1< 0.001
Klebsiella pneumoniae2216.41122.91112.80.149
Streptococcus pneumoniae2216.4510.41719.80.225
Moraxella catarrhalis86.036.355.81.000
Staphylococcus aureus75.224.255.81.000
Legionella pneumophila43.024.222.30.617
VirusesRhinovirus3022.4714.62326.70.132
Influenza B (PCR/FT)1611.9510.41112.80.786
Coronavirus 22975.200.078.10.050
Adenovirus43.000.044.70.296
Influenza A H3 (PCR/FT)43.048.300.00.015
Coronavirus HKU132.236.300.00.044
Coronavirus 6321.500.022.30.537
Parainfluenza 221.500.022.30.537
Parainfluenza 421.500.022.30.537
Coronavirus 4310.712.100.00.358
Negative64.5510.411.20.022

ILI = influenza-like illness; PCR = polymerase chain reaction; URI = upper respiratory illness.

Fisher’s exact test comparing ILI and non-ILI cases.

Tests positive by either reverse transcription polymerase chain reaction or Fast Track multiplex PCR.

Analysis of URI cases by time since the start of follow-up indicated strong temporal clustering of cases, with each cluster involving several respiratory pathogens (Figure 2). For example, the single cluster in Camp A during the November 2014 cohort resulted in identification of both rhinovirus and coronavirus 63, as well as numerous colonizing bacteria. In other clusters, rhinovirus was also identified in combination with parainfluenza viruses, adenovirus, and influenza B virus (Figure 2).

Figure 2.
Figure 2.

Pathogens detected in upper respiratory illness (URI) cases by camp, training cohort, and day of onset relative to the start of follow-up. Size and color of circles indicate number of URI cases in which a given pathogen was detected.

Citation: The American Journal of Tropical Medicine and Hygiene 99, 4; 10.4269/ajtmh.18-0219

Influenza vaccination and seroconversion.

At enrollment, 2.4% of recruits reported having received influenza vaccination in the previous 12 months. In the serology subset, the rate of influenza infection was 3.4 per 100 person-months (Table 3). Thirteen of 169 (8%) recruits seroconverted over the 10-week training period. Seroconversion was most common against influenza B/Massachusetts (N = 7) and influenza A/H3 (N = 3) (Table 3). Median baseline titers were 1:80 (IQR: 1:40–1:160) for influenza B/Massachusetts, 1:40 (IQR: 1:20–1:80) for influenza A/H3, 1:20 (IQR: 1:10–1:40) for influenza A/pdmH1N1, and 1:10 (IQR: 1:10–1:10) for influenza B/Brisbane. There was a strong correlation between baseline and end of follow-up antibody titers, with evidence of low prior exposure to B/Brisbane but high prior exposure to B/Massachusetts (Figure 3). Comparison of overall seroconversion and clinical influenza rates indicated that approximately 58% of influenza infections resulted in clinical disease.

Table 3

Influenza seroconversion rates per 100 person-months among two cohorts of Royal Thai Army recruits entering basic training

Influenza strainCohort 1* (N = 51)Cohort 2 (N = 118)Total (N = 169)
NRate (95% CI)nRate (95% CI)nRate (95% CI)
A/2009020.75 (0.19; 3.00)20.52 (0.13; 2.09)
A/H310.87 (0.12; 6.15)20.75 (0.19; 3.00)30.78 (0.25; 2.43)
B/Massachusetts072.62 (1.25; 5.50)71.83 (0.87; 3.84)
A (unclassified)010.37 (0.05; 2.66)10.26 (0.04; 1.86)
Any10.87 (0.12; 6.15)124.50 (2.55; 7.92)133.40 (1.97; 5.86)

CI = confidence interval.

November 1, 2014–January 9, 2015.

May 1, 2015–July 9, 2015.

Figure 3.
Figure 3.

Distribution of antibody titers as measured by hemagglutinin inhibition assay at baseline (y axis) and follow-up (x axis). The color scale indicates the proportion of sample pairs in each titer combination. Gray squares denote a ≥ 4-fold increase in antibody titer at follow-up. Row totals indicate the probability distribution of baseline titers.

Citation: The American Journal of Tropical Medicine and Hygiene 99, 4; 10.4269/ajtmh.18-0219

Colonization.

At baseline, 82.3% of recruits were colonized with H. influenzae type B and 31.5% with H. influenzae non–type B. Other common colonizing bacteria were K. pneumoniae (14.6%), Staphylococcus aureus (8.5%), and S. pneumoniae (8.5%). At the end of follow-up, colonization with H. influenzae non–type B had increased to 74.1%, and S. pneumoniae to 33.6%, whereas colonization with H. influenzae type B and K. pneumoniae had decreased to 67.2% and 8.4%, respectively. In addition, Moraxella catarrhalis was found in four (3.1%) and L. pneumophila in two (1.5%) end of follow-up samples. No change in S. aureus colonization was found. In a subset of paired baseline and end of follow-up samples initially negative for H. influenzae non–type B (N = 89), the risk of H. influenzae non–type B acquisition was 70.1% (95% CI: 54.4–90.6%). Among those negative for S. pneumoniae at baseline (N = 119), the risk of acquiring S. pneumoniae during the follow-up period was 31.9% (95% CI: 22.6–43.8%).

Use of medications.

Of 248 URI episodes, 39.1% were prescribed antibiotics. Of these, all but one were prescribed amoxicillin or azithromycin. In multivariable logistic regression, cases were more likely to be prescribed antibiotics if they presented with tonsillitis (OR = 5.10, 95% CI: 2.35–11.10), chills (OR = 3.91, 95% CI: 1.44–10.62), and swollen lymph nodes (OR = 2.54, 95% CI: 1.07–6.04). Antibiotic prescription was less likely if patients presented with nasal congestion (OR = 0.26, 95% CI: 0.12–0.54). There was no difference in prescribing between ILI and non-ILI patients. Of 35 URI cases prescribed antibiotics and with available multiplex PCR results, 16 (45.6%) had viral pathogens detected and eight (22.9%) had a bacterial target detected in the absence of other pathogens.

DISCUSSION

We found a high incidence of URI in Thai army recruits, indicating that approximately 30% of recruits experienced a URI episode over the 10-week training period. Comparison with other military cohorts is not straightforward because of differences between settings in terms of vaccination policies and seasonality of key pathogens such as influenza. The URI and ILI rates in our study are nonetheless comparable with those reported by other studies in the United States.1618 Despite this, we found low rates of clinical influenza A in this minimally vaccinated population. Possible reasons for this could be exposure to circulating influenza strains before recruits entering the training camps. Thai national influenza surveillance data indicate high influenza activity in the first half of 2014, with influenza A/H1N1 and influenza B predominating.19 Concomitantly, our data indicated that 55% of recruits with available serological information had baseline influenza A/H1N1 titers ≥ 1:40. Titers greater than this value have been shown to be associated with a 50% reduction in risk of clinical influenza from homologous strains, for both influenza A and B viruses.2023 Of interest, 86% of recruits also had baseline titers against influenza B/Massachusetts greater than this level. The higher baseline titers against influenza B/Massachusetts are consistent with the frequent detection of influenza B isolates from the Yamagata lineage in clinical specimens from Thailand in the first half of 2014.19

In our study, the Fast Track multiplex assay appeared to have lower sensitivity for influenza compared with the CDC RT-PCR assay. We did not specifically investigate reasons for these discrepancies, although it should be noted that the two assays were not performed at the same time, as the multiplex assays were all performed at the end of data collection. We therefore cannot discount the possibility that sample degradation might have influenced the relative performance of the Fast Track assay.

Although influenza incidence was low, pathogen detection with sensitive multiplex diagnostics indicated high frequencies of respiratory pathogens, with co-circulation of multiple viruses including rhinovirus, adenovirus, and coronaviruses as well as influenza. In addition, we found high levels of colonization with numerous bacterial species, including both type B and non–type B H. influenzae, K. pneumoniae, and S. pneumoniae. Although we did not specifically study transmission chains or epidemiologic links between cases of illness, in the context of our study, recruits did not leave the camps during the 10-week training periods, such that the occurrence of respiratory pathogens is most likely to have resulted from transmission within the camps rather than from external sources. Intense transmission of bacterial species was apparent, as the risks of acquiring H. influenzae non–type B and S. pneumoniae among initially non-colonized individuals were 70% and 31%, respectively. Bacterial species were also commonly found in samples from URI cases. The colonizing nature of these bacterial species makes it difficult to determine the clinical relevance of these detections. However, H. influenzae type B and non–type B were identified in 13% and 9% of clinical samples in the absence of any other pathogens, suggesting that these pathogens could be responsible for illness in a fraction of adult URI cases. Interestingly, H. influenzae type B has not been previously associated with a significant burden of URI in adults.24 It is possible, however, that these cases were caused by other pathogens not included in the multiplex assay.

High levels of colonization with bacterial species also point to the need for judicious use of antibiotics to treat URI in military populations. A quarter of URI cases in our study were prescribed broad-spectrum antibiotics, of whom 50% were more likely to have infections caused by viral pathogens based on multiplex PCR results. Although we lacked additional information to determine whether this resulted in adverse antibiotic resistance patterns, high levels of antibiotic use in a population with a high background of bacterial colonization presents a risk for development of antibiotic resistance, and highlights the importance of improved rapid diagnostics to rule out viral etiologies to aid clinical management. In addition, it points to the need for increased antibiotic stewardship and health-care provider education to reduce unnecessary use of antibiotics in military settings.

Our study also emphasizes the importance of systematic microbiological surveillance of URI in military populations, to allow prompt detection and control of outbreaks and early identification of emerging pathogens that may be circulating or could be introduced in the wider population. This is particularly important as infection control options in such closed settings are limited and vaccination coverage for key pathogens is low.

Limited resources meant it was not possible to conduct multiplex diagnostics for all baseline, acute, and end of follow-up samples, as well as influenza serology. As a result, there was limited power to investigate whether colonization influenced risk of illness, or factors associated with colonization and acquisition of bacteria. In addition, co-circulation of multiple pathogens makes it difficult to establish chains of transmission, which would require more detailed microbial sequencing information. Clinical signs and symptoms were available at presentation only, and we did not have information regarding the duration of individual symptoms or additional clinical investigations conducted longitudinally during the course of illness, as these were not routinely performed.

The specific barracks setting and population characteristics limit the generalizability of our findings to other military settings with similar conditions. Nevertheless, our study provides key data regarding the epidemiology and transmission of respiratory pathogens in military populations in tropical settings. Our results emphasize the need for improved infection prevention and control strategies in military settings, given the potential for intense transmission of a wide range of respiratory pathogens.

Supplementary Material

Acknowledgments:

We are grateful to the military recruits who participated in the study, the Royal Thai Army, and the clinical, laboratory, and administrative personnel at AFRIMS for their support.

REFERENCES

  • 1.

    Korzeniewski K, Nitsch-Osuch A, Konior M, Lass A, 2015. Respiratory tract infections in the military environment. Respir Physiol Neurobiol 209: 7680.

    • Search Google Scholar
    • Export Citation
  • 2.

    Korzeniewski K, Nitsch-Osuch A, Chciałowski A, Korsak J, 2013. Environmental factors, immune changes and respiratory diseases in troops during military activities. Respir Physiol Neurobiol 187: 118122.

    • Search Google Scholar
    • Export Citation
  • 3.

    Chen MIC et al. 2010. 2009 influenza A(H1N1) seroconversion rates and risk factors among distinct adult cohorts in Singapore. JAMA 303: 13831391.

    • Search Google Scholar
    • Export Citation
  • 4.

    Cheng J et al. 2016. Epidemiology and transmission characteristics of human adenovirus type 7 caused acute respiratory disease outbreak in military trainees in east China. Am J Transl Res 8: 23312342.

    • Search Google Scholar
    • Export Citation
  • 5.

    Yoo H et al. 2017. Febrile respiratory illness associated with human adenovirus type 55 in South Korea military, 2014–2016. Emerg Infect Dis 23: 10161020.

    • Search Google Scholar
    • Export Citation
  • 6.

    Yu P, Ma C, Nawaz M, Han L, Zhang J, Du Q, Zhang L, Feng Q, Wang J, Xu J, 2013. Outbreak of acute respiratory disease caused by human adenovirus type 7 in a military training camp in Shaanxi, China. Microbiol Immunol 57: 553560.

    • Search Google Scholar
    • Export Citation
  • 7.

    Halhal B, Glick Y, Galor I, Ran A, Bacon DJ, Glassberg E, 2017. Pertussis outbreak among soldiers during basic training: the need for updated protocols. Mil Med 182: 355359.

    • Search Google Scholar
    • Export Citation
  • 8.

    Clemmons NS, McCormic ZD, Gaydos JC, Hawksworth AW, Jordan NN, 2017. Acute respiratory disease in US army trainees 3 years after reintroduction of adenovirus vaccine. Emerg Infect Dis 23: 9598.

    • Search Google Scholar
    • Export Citation
  • 9.

    Gray J, Coupland LJ, 2014. The increasing application of multiplex nucleic acid detection tests to the diagnosis of syndromic infections. Epidemiol Infect 142: 111.

    • Search Google Scholar
    • Export Citation
  • 10.

    Reddington K, Tuite N, Barry T, O’Grady J, Zumla A, 2013. Advances in multiparametric molecular diagnostics technologies for respiratory tract infections. Curr Opin Pulm Med 19: 298304.

    • Search Google Scholar
    • Export Citation
  • 11.

    Levy JW et al. 2015. Elevated transmission of upper respiratory illness among new recruits in military barracks in Thailand. Influenza Other Respir Viruses 9: 308314.

    • Search Google Scholar
    • Export Citation
  • 12.

    World Health Organization, 2009. CDC Protocol of Realtime RTPCR for Influenza A(H1N1). Available at: http://www.who.int/csr/resources/publications/swineflu/CDCRealtimeRTPCR_SwineH1Assay-2009_20090430.pdf. Accessed March 14, 2018.

  • 13.

    Centers for Disease Control and Prevention, 2007. CDC Realtime RT-PCR (rRTPCR) Protocol for Detection and Characterization of Influenza. Atlanta, GA: CDC.

  • 14.

    Salez N, Vabret A, Leruez-Ville M, Andreoletti L, Carrat F, Renois F, de Lamballerie X, 2015. Evaluation of four commercial multiplex molecular tests for the diagnosis of acute respiratory infections. PLoS One 10: e0130378.

    • Search Google Scholar
    • Export Citation
  • 15.

    Sakthivel SK, Whitaker B, Lu X, Oliveira DBL, Stockman LJ, Kamili S, Oberste MS, Erdman DD, 2012. Comparison of fast-track diagnostics respiratory pathogens multiplex real-time RT-PCR assay with in-house singleplex assays for comprehensive detection of human respiratory viruses. J Virol Methods 185: 259266.

    • Search Google Scholar
    • Export Citation
  • 16.

    Millar EV, Schlett CD, Law NN, Chen W-J, D’Onofrio MJ, Bennett JW, Tribble DR, Ellis MW, 2016. Reduction in acute respiratory infection among military trainees: secondary effects of a hygiene-based cluster-randomized trial for skin and soft-tissue infection prevention. Infect Control Hosp Epidemiol 37: 11181120.

    • Search Google Scholar
    • Export Citation
  • 17.

    Phillips CJ, Woolpert T, Sevick C, Faix D, Blair PJ, Crum-Cianflone NF, 2013. Comparison of the effectiveness of trivalent inactivated influenza vaccine and live, attenuated influenza vaccine in preventing influenza-like illness among US military service members, 2006–2009. Clin Infect Dis 56: 1119.

    • Search Google Scholar
    • Export Citation
  • 18.

    Ryan MA, Christian RS, Wohlrabe J, 2001. Handwashing and respiratory illness among young adults in military training. Am J Prev Med 21: 7983.

    • Search Google Scholar
    • Export Citation
  • 19.

    Prachayangprecha S, Vichaiwattana P, Korkong S, Felber JA, Poovorawan Y, 2015. Influenza activity in Thailand and occurrence in different climates. Springerplus 4: 356.

    • Search Google Scholar
    • Export Citation
  • 20.

    Hobson D, Curry RL, Beare AS, Ward-Gardner A, 1972. The role of serum haemagglutination-inhibiting antibody in protection against challenge infection with influenza A2 and B viruses. J Hyg (Lond) 70: 767777.

    • Search Google Scholar
    • Export Citation
  • 21.

    Potter CW, Oxford JS, 1979. Determinants of immunity to influenza infection in man. Br Med Bull 35: 6975.

  • 22.

    Ng S, Fang VJ, Ip DKM, Chan K-H, Leung GM, Peiris JSM, Cowling BJ, 2013. Estimation of the association between antibody titers and protection against confirmed influenza virus infection in children. J Infect Dis 208: 13201324.

    • Search Google Scholar
    • Export Citation
  • 23.

    Coudeville L, Bailleux F, Riche B, Megas F, Andre P, Ecochard R, 2010. Relationship between haemagglutination-inhibiting antibody titres and clinical protection against influenza: development and application of a bayesian random-effects model. BMC Med Res Methodol 10: 18.

    • Search Google Scholar
    • Export Citation
  • 24.

    Agrawal A, Murphy TF, 2011. Haemophilus influenzae infections in the H. influenzae type b conjugate vaccine era. J Clin Microbiol 49: 37283732.

    • Search Google Scholar
    • Export Citation

Author Notes

Address correspondence to Clarence C. Tam, Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Dr. 2, Singapore 117549, Singapore. E-mail: clarence.tam@nus.edu.sg

Financial support: This work was supported by the United States Department of Defense—Global Emerging Infectious Disease Surveillance (DoD—GEIS), Protocol 989A.

Disclosures: The authors declare that they have no competing interests. Material has been reviewed by the Walter Reed Army Institute of Research. There is no objection to its presentation and/or publication. The opinions or assertions contained herein are the private views of the author, and are not to be construed as official, or as reflecting true views of the Department of the Army or the Department of Defense. The investigators have adhered to the policies for protection of human subjects as prescribed in AR 70-25.

Authors’ addresses: Clarence C. Tam, Saw Swee Hock School of Public Health, National University of Singapore and National University Health Systems, Singapore, Singapore, and London School of Hygiene & Tropical Medicine, London, United Kingdom, E-mail: clarence.tam@nus.edu.sg. Kathryn B. Anderson, University of Minnesota, Minneapolis, MN, E-mail: kathryn.anderson.ctr@afrims.org. Vittoria Offeddu, Saw Swee Hock School of Public Health, National University of Singapore and National University Health Systems, Singapore, Singapore, E-mail: vittoria.offeddu@nus.edu.sg. Alden Weg, Louis R. Macareo, Damon W. Ellison, and Stefan Fernandez, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand, E-mails: alden.weg.mil@afrims.org, louis.macareo.mil@afrims.org, damon.ellison.mil@afrims.org, and stefan.fernandez.mil@mail.mil. Ram Rangsin, Phramongkutklao College of Medicine, Bangkok, Thailand, E-mail: r_rangsin@yahoo.com. Robert V. Gibbons, University of Texas at San Antonio, San Antonio, TX, E-mail: robertvgibbons@gmail.com. In-Kyu Yoon, International Vaccine Institute, Seoul, Korea, E-mail: inkyu.yoon@ivi.int. Sriluck Simasathien, Phramongkutklao Hospital, Bangkok, Thailand, E-mail: ssriluck@hotmail.com.

Save