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    Figure 1.

    Proportion with respiratory viruses identified, by age category, among patients hospitalized with acute febrile illness, southern Sri Lanka, 2012–2014.

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    Figure 2.

    Respiratory virus (A), influenza A (B), and influenza B (C) seasonality using the program for appropriate technology definition among patients hospitalized with acute febrile illness in southern Sri Lanka, 2012–2014.

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Respiratory Viral Infection: An Underappreciated Cause of Acute Febrile Illness Admissions in Southern Sri Lanka

L. Gayani TillekeratneDuke University, Durham, North Carolina;
Duke Global Health Institute, Durham, North Carolina;
Duke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka;

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Champica K. BodinayakeDuke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka;
Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka;

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Ryan SimmonsDuke Global Health Institute, Durham, North Carolina;

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Ajith NagahawatteDuke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka;
Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka;

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Vasantha DevasiriDuke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka;
Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka;

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Wasantha Kodikara ArachchiDuke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka;
Teaching Hospital Karapitiya, Galle, Sri Lanka;

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Bradly P. NicholsonDuke University, Durham, North Carolina;
Duke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka;

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Lawrence P. ParkDuke University, Durham, North Carolina;
Duke Global Health Institute, Durham, North Carolina;

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Sky VanderburgDuke University, Durham, North Carolina;
Duke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka;

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Ruvini KurukulasooriyaDuke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka;

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Aruna Dharshan De SilvaDuke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka;
General Sir Kotelawala Defence University, Ratmalana, Sri Lanka

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Truls ØstybeDuke University, Durham, North Carolina;
Duke Global Health Institute, Durham, North Carolina;
Duke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka;

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Megan E. RellerDuke University, Durham, North Carolina;
Duke Global Health Institute, Durham, North Carolina;
Duke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka;

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Christopher W. WoodsDuke University, Durham, North Carolina;
Duke Global Health Institute, Durham, North Carolina;
Duke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka;

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The contribution of respiratory viruses to acute febrile illness (AFI) burden is poorly characterized. We describe the prevalence, seasonality, and clinical features of respiratory viral infection among AFI admissions in Sri Lanka. We enrolled AFI patients ≥ 1 year of age admitted to a tertiary care hospital in southern Sri Lanka, June 2012–October 2014. We collected epidemiologic/clinical data and a nasal or nasopharyngeal sample that was tested using polymerase chain reaction (Luminex NxTAG, Austin, TX). We determined associations between weather data and respiratory viral activity using the Spearman correlation and assessed respiratory virus seasonality using a Program for Appropriate Technology definition. Bivariable and multivariable regression analyses were conducted to identify features associated with respiratory virus detection. Among 964 patients, median age was 26.2 years (interquartile range 14.6–39.9) and 646 (67.0%) were male. One-fifth (203, 21.1%) had respiratory virus detected: 13.9% influenza, 1.4% human enterovirus/rhinovirus, 1.4% parainfluenza virus, 1.1% respiratory syncytial virus, and 1.1% human metapneumovirus. Patients with respiratory virus identified were younger (median 9.8 versus 27.7 years, P < 0.001) and more likely to have respiratory signs and symptoms. Influenza A and respiratory viral activity peaked in February–June each year. Maximum daily temperature was associated with influenza and respiratory viral activity (P = 0.03 each). Patients with respiratory virus were as likely as others to be prescribed antibiotics (55.2% versus 52.6%, P = 0.51), and none reported prior influenza vaccination. Respiratory viral infection was a common cause of AFI. Improved access to vaccines and respiratory diagnostics may help reduce disease burden and inappropriate antibiotic use.

INTRODUCTION

Acute febrile illness (AFI) or fever without localizing signs is a common reason for hospitalization in tropical and subtropical settings.1 Acute febrile illness etiology varies widely by geographic region, season, and climate, and is challenging to identify based on clinical features alone.2 Confirmation of diagnoses with laboratory testing is essential, but many settings lack the necessary infrastructure.3 Acute febrile illness etiologies such as malaria and dengue, which carry high morbidity and mortality and are of considerable public health interest, thus become the focus of many diagnostic clinical laboratories.4 Other diseases implicated in AFI may consequently be underdiagnosed and inappropriately managed.2

The contribution of respiratory viruses to global AFI burden is not well described in the literature.1 Influenza affects 10–20% of the world’s population annually, and other viruses such as respiratory syncytial virus (RSV), parainfluenza virus (PIV), and human rhinovirus/enterovirus (HRV/HEV) as a group account for even greater annual morbidity and mortality.5 Respiratory illnesses account for most of the acute infections at all ages, but few AFI studies have incorporated respiratory viral testing into the diagnostic panel.6

In 2007, we determined the burden of AFI due to dengue, rickettsial infections, leptospirosis, and chikungunya among patients presenting to a tertiary care hospital in southern Sri Lanka.710 Respiratory viral testing was not performed and more than 50% of patients did not receive a laboratory-confirmed diagnosis. In the present study, we repeated surveillance for AFI in southern Sri Lanka from 2012 to 2014. We determined the prevalence, seasonality, and clinical features of respiratory viral infection among patients admitted with AFI.

MATERIALS AND METHODS

Study population.

We prospectively enrolled patients with AFI admitted to the pediatric and adult wards of the largest (1,500 bed) tertiary care hospital in the southern province of Sri Lanka from June 2012 to October 2014. Consecutive patients ≥ 1 year of age with documented fever (> 38°C) at presentation or within 48 hours of hospital admission were eligible. We obtained epidemiological and clinical data and a nasopharyngeal sample at enrollment. Patients who did not tolerate nasopharyngeal sampling had a nasal sample collected instead. Details regarding patients’ clinical management and outcomes during hospitalization were subsequently extracted from the medical record.

Respiratory pathogen molecular testing.

The upper respiratory sample collected from each patient was placed in viral transport media and frozen at −80°C. The nasal or nasopharyngeal sample of alternate (i.e., every other) enrolled patient was selected for testing by real-time reverse transcription–polymerase chain reaction (PCR) with the Luminex Integrated System NxTAG Respiratory Pathogen Panel platform. If a patient did not have a nasal or nasopharyngeal specimen collected, the next alternate patient was selected for testing. The Luminex platform detects 19 respiratory viruses (RSV A and B; nonspecific influenza A; influenza A subtypes H1, H3, and 2009 H1N1; influenza B; parainfluenza 1–4; human metapneumovirus (hMPV); adenovirus; HRV/HEV; coronavirus types NL63, HKU1, 229E, and OC43; and human bocavirus) and three bacteria (Chlamydophila pneumoniae, Legionella pneumophila, and Mycoplasma pneumoniae).11

Statistical analysis.

Seasonality of influenza and all respiratory viruses was determined using a definition from the Program for Appropriate Technology (PATH).12 The monthly proportion of cases of influenza out of all positive cases of influenza for a given calendar year was calculated. A “peak” in activity was defined as the monthly proportion being ≥ 10% during two consecutive years. If circulation varied from year to year (i.e., proportion < 10% per month), then a peak was not identified according to the definition. The PATH methodology was also used to determine seasonality of all respiratory viruses as a group.

Monthly weather data were obtained for the Galle region from the Sri Lanka Department of Meteorology.13 Correlation between weather data (monthly rainfall, monthly minimum temperature, monthly maximum temperature, daytime humidity, and nighttime humidity) and the monthly proportion of subjects with influenza or respiratory viruses was determined using the Spearman correlation.14

Sociodemographic and clinical characteristics of patients with a positive compared with a negative respiratory viral test were compared using the Fisher exact test for categorical variables and the Kruskall–Wallis test for continuous variables. Bivariable and multivariable logistic regressions were carried out to determine the association (odds ratios [OR] with 95% confidence intervals [CI]) between patients’ sociodemographic and clinical characteristics, and having a positive respiratory viral PCR test result. Tachypnea was defined as > 40 breaths/minute for children aged 1 to < 5 years, and > 20 breaths/minute for children aged ≥ 5 years and adults.15 Tachycardia was defined as > 180 beats/minute for children aged 1 to < 2 years, > 140 beats/minute for children aged 2 to < 6 years, > 130 beats/minute for children aged 6 to < 13 years, > 110 beats/minute for children aged 13 to < 18 years, and > 100 beats/minute for adults ≥ 18 years.16

For the multivariable analysis, an adjusted model was constructed to determine features associated with respiratory viral infection. Any sociodemographic characteristic, clinical symptom, or examination finding that was associated with the dependent variable at a P-value < 0.25 on bivariable analysis was a candidate for inclusion in the multivariable model. Variables were checked for collinearity and nonlinear relationships before inclusion in the model. To create a more parsimonious model, Bayesian model averaging was performed.17 The multivariable model was constructed by adding the variables with the highest posterior inclusion probabilities until an effect was no longer significant. To check for confounding and moderation, excluded variables and interaction effects were then added into the final model sequentially.

All analyses were performed using STATA, version 11 (STATACorp, College Station, TX). Bayesian model averaging was performed using the BMA package in R, version 3.3.3(Vienna, Austria).

Written informed consent was obtained from all patients and from parents or guardians of minors. The Institutional Review Boards of the University of Ruhuna Faculty of Medicine (Sri Lanka), Duke University Medical Center (Durham, NC), and Johns Hopkins University (Baltimore, MD) approved this study.

RESULTS

Study cohort and respiratory testing results.

Of 1,954 patients enrolled from June 2012 to October 2014, 968 patients had upper respiratory samples collected and tested. Of these, four had an invalid respiratory test result and were excluded from further analyses. For the remaining 964 patients, the median age was 26.2 years (IQR 14.6–39.9 years) and 135 patients (14.0%) were aged < 5 years. The majority (646, 67.0%) were male. A total of 205 (21.3%) patients had an upper respiratory sample that tested positive for a respiratory organism, with all but two of the detected organisms being viruses (Table 1). The most commonly detected pathogen was influenza for both adults and children (134, 13.9% of all tested patients), with approximately two-thirds being influenza A and the remainder being influenza B. Other viruses identified included HRV/HEV (1.4% of tested patients), PIV (1.4%), RSV (1.1%), hMPV (1.1%), and bocavirus (0.7%). Respiratory coinfections were identified in 0.7% of patients. Children aged < 5 years were more likely to have respiratory virus identified and to have a respiratory coinfection compared with patients aged ≥ 5 years (Table 1, Figure 1). Severity of disease in the tested patients was low, with five (0.5%) patients requiring intensive unit care, two (0.2%) requiring vasopressors, two (0.2%) requiring intubation, and seven (0.7%) patients dying. None of the patients with severe illness had a respiratory pathogen detected.

Table 1

Organisms identified from the upper respiratory tract in patients admitted with acute febrile illness, southern Sri Lanka, 2012–2014

Virus typeNumber (%) in all patientsNumber (%) in patients aged < 5 yearsNumber (%) in patients aged ≥ 5 yearsP-value
Influenza A88 (9.1)14 (10.8)74 (8.9)0.49
 H1N1p200937 (3.8)8 (6.2)29 (3.5)0.14
 H344 (4.6)6 (4.6)38 (4.6)0.98
 Untypeable7 (0.7)7 (0.8)0.29
Influenza B46 (4.8)7 (5.4)39 (4.7)0.73
Parainfluenza virus13 (1.4)11 (8.5)2 (0.2)< 0.001
 Parainfluenza 13 (0.3)2 (1.5)1 (0.1)0.007
 Parainfluenza 22 (0.2)2 (1.5)< 0.001
 Parainfluenza 38 (0.8)7 (5.4)1 (0.1)< 0.001
Human rhinovirus/enterovirus13 (1.4)8 (6.2)5 (0.6)< 0.001
Human metapneumovirus11 (1.1)6 (4.6)5 (0.6)< 0.001
RSV11 (1.1)10 (7.7)1 (0.1)< 0.001
 RSV A6 (0.6)6 (4.6)< 0.001
 RSV B5 (0.5)4 (3.1)1 (0.1)< 0.001
Bocavirus7 (0.7)4 (3.1)3 (0.4)< 0.001
Adenovirus5 (0.5)4 (3.1)1 (0.1)< 0.001
Coronavirus2 (0.2)1 (0.1)0.69
Mycoplasma pneumoniae1 (0.1)1 (0.1)0.69
Chlamydophila pneumoniae1 (0.1)1 (0.1)0.69
Co-infections7 (0.7)4 (3.1)3 (0.4)< 0.001
Negative759 (78.7)62 (47.7)696 (83.6)< 0.001
Total964130833

RSV = respiratory syncytial virus. P < 0.15 listed in bold.

Figure 1.
Figure 1.

Proportion with respiratory viruses identified, by age category, among patients hospitalized with acute febrile illness, southern Sri Lanka, 2012–2014.

Citation: The American Journal of Tropical Medicine and Hygiene 100, 3; 10.4269/ajtmh.18-0699

Seasonality of respiratory viruses and associated weather parameters.

Respiratory viral activity peaked in February–June of both 2013 and 2014 (excluding the month of March; Figure 2A). Influenza A activity also peaked during these same months (Figure 2B), whereas influenza B activity peaked in July 2012 and 2013 (Figure 2C). Of weather parameters, only maximum daily temperature was correlated with either respiratory virus or influenza detection: r = 0.42 (95% CI: 0.05–0.68, P = 0.03) for all respiratory viruses and r = 0.42 (95% CI: 0.05–0.68, P = 0.03) for influenza. Rainfall (r = −0.24, 95% CI: −0.56 to 0.15, P = 0.22), minimum daily temperature (r = 0.29, 95% CI: −0.10 to 0.60, P = 0.14), daytime humidity (r = −0.11, 95% CI: −0.46 to 0.28, P = 0.59), and nighttime humidity (r = −0.14, 95% CI: −0.49 to 0.25, P = 0.49) were not correlated with respiratory virus activity. Rainfall (r = −0.29, 95% CI: −0.60 to 0.09, P = 0.13), minimum daily temperature (r = 0.23, 95% CI: −0.16 to 0.55, P = 0.25), daytime humidity percentage (r = −0.21, 95% CI: −0.54 to 0.17, P = 0.28), and nighttime humidity percentage (r = −0.19, 95% CI: −0.53 to 0.20, P = 0.34) were also not correlated with influenza activity.

Figure 2.
Figure 2.

Respiratory virus (A), influenza A (B), and influenza B (C) seasonality using the program for appropriate technology definition among patients hospitalized with acute febrile illness in southern Sri Lanka, 2012–2014.

Citation: The American Journal of Tropical Medicine and Hygiene 100, 3; 10.4269/ajtmh.18-0699

Sociodemographic and clinical features associated with respiratory viral infection.

Results of the bivariable associations of sociodemographic characteristics, exposures, and clinical features with respiratory viral infection are shown in Table 2. The two patients with bacterial respiratory pathogens on testing were excluded from the analysis. Patients with respiratory virus identified were younger than patients with no respiratory virus (median age 9.8 versus 27.7 years, P < 0.001) and were more likely to report a sick contact within the prior 4 weeks (OR 1.51, 95% CI: 1.08–2.10). Clinical symptoms were different in patients with and without respiratory virus identified. Patients with respiratory virus had a shorter duration of fever (median 4 versus 5 days, P < 0.001) and were more likely to report respiratory symptoms such as rhinitis/congestion (OR 6.40, 95% CI: 4.54–9.03), cough (OR 4.80, 95% CI: 3.36–6.85), and shortness of breath (OR 1.91, 95% CI: 1.24–2.95). However, the duration of cough was shorter in patients who had respiratory virus identified than in those who did not. Patients with respiratory virus identified were also less likely to report nonspecific symptoms such as fatigue, joint pain, muscle pain, and headache. On physical examination, patients with respiratory virus were more likely to have crepitations (OR 3.15, 95% CI: 2.18–4.54) and rhonchi/wheezing (OR 5.63, 95% CI: 3.36–9.42) than patients with no respiratory virus identified. Other examination findings, such as hepatomegaly, tender liver, and rash, were significantly less common in patients with respiratory virus than those without respiratory virus.

Table 2

Bivariable analysis of sociodemographic characteristics, exposures, and clinical features associated with respiratory virus detection among patients admitted with acute febrile illness, southern Sri Lanka, 2012–2014

CharacteristicNumber (%) or median (IQR) in RVP+ (n = 203)Number (%) or median (IQR) in RVP− (n = 761)Odds ratio (95% confidence interval)P-value
Sociodemographic characteristics and exposures
Age (years)9.8 (3.9–30.5)27.7 (18.4–41.1)0.97 (0.96, 0.98)< 0.001
Male125 (61.6)521 (68.5)0.74 (0.54–1.02)0.06
Occupation (adults)
Unemployed/retired24 (27.0)133 (22.8)Reference0.79
 Laborer32 (36.0)221 (37.9)0.80 (0.45, 1.42)
 Merchant/office12 (13.5)94 (16.1)0.71 (0.34, 1.49)
 Other16 (18.0)98 (16.8)0.91 (0.46, 1.79)
Education ≥ 12th grade (adults)30 (33.7)209 (35.8)0.91 (0.57–1.47)0.71
Common hometown
 Galle45 (22.2)142 (18.7)Reference0.71
 Akuressa5 (2.5)29 (3.8)0.54 (0.20, 1.49)
 Ahangama7 (3.5)24 (3.2)0.92 (0.37, 2.28)
 Wanduramba8 (3.9)37 (4.9)0.68 (0.30, 1.57)
 Poddala6 (3.0)26 (3.4)0.73 (0.28, 1.88)
Sick contact in past 4 weeks72 (35.1)199 (26.3)1.52 (1.08–2.14)0.01
Travel in past 4 weeks21 (10.3)144 (18.9)0.49 (0.30–0.80)0.004
Rural residence46 (22.7)143 (18.8)1.27 (0.87–1.84)0.22
Passive or active smoking40 (19.7)222 (29.2)0.60 (0.41–0.87)0.008
Prior antibiotic use60 (29.6)194 (25.5)0.93 (0.64, 1.33)0.68
Clinical features
 Days of fever4 (3–5)5 (3–6)0.88 (0.82, 0.94)< 0.001
Rhinitis/congestion103 (50.7)106 (13.9)6.40 (4.54–9.03)< 0.001
 Cough153 (75.4)299 (39.3)4.80 (3.36–6.85)< 0.001
 Days of cough4 (3–5)4 (3–6)1.13 (1.08, 1.18)< 0.001
 Sore throat36 (17.7)112 (14.7)1.27 (0.84–1.91)0.26
 Shortness of breath35 (17.2)75 (9.9)1.91 (1.24–2.95)0.004
 Pain with breathing17 (8.4)69 (9.1)0.93 (0.53–1.62)0.79
 Decreased appetite146 (71.9)568 (74.6)0.88 (0.62–1.24)0.44
 Vomiting82 (40.4)354 (46.5)0.76 (0.56–1.05)0.09
 Diarrhea18 (8.9)133 (17.5)0.46 (0.27–0.77)0.003
 Abdominal pain31 (15.3)156 (20.5)0.71 (0.47–1.08)0.11
 Decreased urine output12 (5.9)60 (7.9)0.73 (0.39–1.39)0.34
 Dysuria7 (3.4)78 (10.2)0.31 (0.14–0.69)0.004
 Headache112 (55.2)548 (72.0)0.48 (0.35–0.66)< 0.001
 Fatigue100 (49.3)470 (61.8)0.60 (0.44–0.82)0.002
 Joint pain68 (33.5)437 (57.4)0.38 (0.27–0.52)< 0.001
 Muscle pain79 (38.9)451 (59.3)0.44 (0.32–0.61)< 0.001
 Admission temperature102.0 (100.4–102.6)102.0 (100.2–102.4)1.01 (0.39–2.65)0.99
 Tachycardia on exam60 (29.6%)265 (34.9%)0.80 (0.57–1.11)0.15
 Tachypnea on exam77 (37.9%)298 (39.2%)0.95 (0.67, 1.34)0.95
 Oxygen saturation on exam99 (98–100)99 (98–100)1.02 (0.94–1.10)0.60
 Conjunctival injection18 (8.9)135 (17.7)0.45 (0.27–0.76)0.003
 Throat erythema10 (4.9)41 (5.4)0.91 (0.45–1.85)0.79
 Enlarged lymph nodes26 (12.8)81 (10.6)1.24 (0.77–1.99)0.37
 Crepitations on exam64 (31.5)97 (12.7)3.15 (2.18–4.54)< 0.001
 Rhonchi/wheezing on exam37 (18.2)29 (3.8)5.63 (3.36–9.42)< 0.001
 Enlarged liver on exam5 (2.5)47 (6.2)0.38 (0.15–0.98)0.04
 Tender liver2 (1.0)50 (6.6)0.14 (0.03–0.59)0.007
 Enlarged spleen1 (0.5)20 (2.6)0.18 (0.02–1.37)0.10
 Rash on exam9 (4.4)102 (13.4)0.30 (0.15–0.60)< 0.001

RVP = respiratory virus positive. P < 0.15 listed in bold.

After adjusting for other sociodemographic and clinical factors in the multivariable regression model, age < 5 years was associated with higher odds of respiratory viral infection (OR 3.62, 95% CI: 2.05–6.43) compared with age 5–65 years (Table 3). Increasing white blood cell count, diarrhea, and the presence of rash on examination were also negatively associated with respiratory viral infection. By contrast, respiratory signs and symptoms including cough, rhinitis/congestion, and rhonchi/wheezing on examination were associated with having respiratory virus. Interestingly, among patients who had cough, increasing duration of cough was negatively associated with having respiratory virus (OR 0.83, 95% CI: 0.75–0.92).

Table 3

Multivariable analysis of sociodemographic features, exposures, and clinical characteristics associated with respiratory virus detection among patients admitted with acute febrile illness, southern Sri Lanka, 2012–2014

VariableOdds ratio (95% confidence interval)P-values
Age < 5 years*3.62 (2.05–6.43)< 0.0001
Age > 65 years*1.25 (0.47–3.03)0.6430
White blood cell count (cells/uL)†0.96 (0.92–0.99)0.0165
Cough5.88 (3.20–10.80)< 0.0001
Cough × days of cough‡0.84 (0.76–0.93)0.0014
Rhinitis/congestion3.16 (2.02–4.95)< 0.0001
Diarrhea0.51 (0.27–0.92)0.0319
Joint pain0.58 (0.38–0.87)0.0083
Rhonchi/wheezing on exam3.16 (1.63–6.16)0.0007
Rash on exam0.27 (0.11–0.59)0.0025

* Reference category: age 5–65 years.

† Within 48 hours of admission; per 1-unit increase.

‡ Per 1-unit increase.

Clinical management of patients with respiratory viral infection.

Patients with respiratory virus identified were more likely to receive a clinical diagnosis of upper respiratory tract infection (OR 1.95, 95% CI: 1.05–3.62), lower respiratory tract infection (OR 3.60, 95% CI: 2.41–5.37), or unspecified viral fever on admission (OR 1.42, 95% CI: 1.04–1.94; Table 4). However, patients with respiratory virus detected were equally likely as other patients to receive antibiotic therapy at enrollment (55.2% versus 52.6%), with the most common antibiotics prescribed being erythromycin, second-generation cephalosporins, and penicillins. Patients with respiratory virus detected had a higher leukocyte count within 48 hours of admission (7.7 versus 5.9 × 103 cells/μL) and were as likely as patients without respiratory virus to have a chest X-ray obtained during hospitalization (25.1% versus 24.8%) or to have an abnormality on chest X-ray (8.4% versus 7.6%). Patients with respiratory virus detected were hospitalized for a shorter duration (4 versus 5 days, P < 0.001) than patients without respiratory virus. Two patients in the entire cohort reported a prior history of influenza vaccination, with both these patients testing negative for respiratory virus.

Table 4

Clinical management and outcomes of patients with and without respiratory virus isolated among a cohort with acute febrile illness, southern Sri Lanka, 2012–2014

CharacteristicNumber (%) or median (IQR) in RVP+ (n = 203)Number (%) or median (IQR)in RVP− (n = 761)Odds ratio (95% confidence interval)P-value
Clinical diagnosis at admission
 Dengue21 (10.3)226 (29.7)0.27 (0.17– 0.44)< 0.001
 Viral fever98 (48.3)301 (39.6)1.42 (1.04–1.94)0.03
 Leptospirosis8 (3.9)103 (13.5)0.26 (0.13–0.55)< 0.001
 Atypical pneumonia4 (2.0)6 (0.8)2.53 (0.71–9.04)0.15
 Upper resp infection16 (7.9)32 (4.2)1.95 (1.05–3.62)0.04
 Lower resp infection53 (26.1)68 (8.9)3.60 (2.41–5.37)< 0.001
Antibiotic therapy at enrollment112 (55.2)400 (52.6)1.11 (0.81–1.52)0.51
 Penicillin21 (10.3)107 (14.1)0.73 (0.45–1.21)0.22
 2nd generation cephalosporin27 (13.3)38 (5.0)2.92 (1.74–4.91)< 0.001
 3rd generation cephalosporin17 (8.4)86 (11.3)0.72 (0.42–1.24)0.23
 Erythromycin37 (18.2)86 (11.3)1.75 (1.15, 2.67)0.01
 Doxycycline2 (1.0)59 (7.8)0.12 (0.03–0.49)0.003
Chest X-ray obtained51 (25.1)189 (24.8)1.02 (0.71–1.45)0.93
Chest X-ray abnormality17 (8.4)58 (7.6)1.13 (0.58–2.18)0.72
 Alveolar15 (7.4)56 (7.4)1.03 (0.52–2.04)0.97
 Interstitial2 (1.0)1 (0.1)7.71 (0.68–87.52)0.94
 Multilobular involvement5 (2.5)5 (0.7)4.00 (1.11, 14.40)0.03
 Effusion1 (0.5)8 (1.1)0.45 (0.06–3.70)0.46
White blood cell count (×103 cells/μL)*7.7 (5.9–10.5)5.9 (3.6–10.2)1.02 (0.99, 1.04)0.09
Leukocytosis*55 (27.1)201 (26.4)1.16 (0.81–1.65)0.42
C-reactive protein performed*51 (25.1)150 (19.7)1.37 (0.95–1.97)0.09
High CRP (> 8 mg/L)*34 (16.8)114 (15.0)1.14 (0.75–1.74)0.53
Hospitalization duration4 (3–5)5 (4–6)0.86 (0.79, 0.93)< 0.001
Intensive unit care0 (0)5 (0.7)n/a0.98
Intubation0 (0)2 (0.3)n/a0.99
Supplemental oxygen use1 (0.5)6 (0.8)0.62 (0.08–5.20)0.66
Use of vasopressors0 (0)2 (0.3)n/a0.99
Clinical diagnosis at discharge
 Dengue10 (4.9)229 (30.1)0.12 (0.06–0.23)< 0.001
 Viral fever83 (40.9)225 (29.6)1.66 (1.21–2.29)0.002
 Leptospirosis9 (4.4)86 (11.3)0.37 (0.18–0.74)0.005
 Atypical pneumonia4 (2.0)7 (0.9)2.18 (0.63–7.51)0.22
 Upper resp infection18 (8.9)26 (3.4)2.76 (1.48–5.14)0.001
 Lower resp infection60 (29.6)67 (8.8)4.38 (2.96–6.48)< 0.001
Antibiotics given at discharge
 Yes47 (23.2)155 (20.4)1.13 (0.76–1.67)0.68
 Unsure25 (12.3)87 (11.4)1.07 (0.65–1.75)0.98
Death0 (0)7 (0.9)n/a0.98

n/a = not applicable; RVP = respiratory virus positivity. P-values in cells with 0 are calculated from Chi-square tests. P < 0.15 listed in bold.

* Within 48 hours of admission.

DISCUSSION

In this study, one-fifth of patients hospitalized with AFI in southern Sri Lanka had a respiratory virus identified. Definite seasonal variation in respiratory viral and influenza A activity was seen, with peak activity in February through June. Patients with respiratory virus isolated had less severe illness than patients with other causes of AFI, with fewer days of fever and shorter duration of hospitalization, and were more likely to report respiratory signs and symptoms. More than half of the patients with respiratory viral illnesses were treated with antibiotics at enrollment, suggesting an inappropriate use of antibiotics. In addition, no patients with respiratory virus reported a history of influenza vaccination, indicating a possible target for future public health intervention.

Few other studies have described the contribution of respiratory viruses to AFI, and most of these studies have focused on influenza alone or on outpatients, who generally have less severe disease. In the Asian-Pacific region, influenza A accounted for 11.8% of outpatients with AFI.18 In Vietnam, respiratory viruses accounted for 10% of AFI among outpatients, with PIV and influenza B being most common.19 In Ghana, Jones et al.20 showed that influenza accounted for 6% of AFI among patients hospitalized at three hospitals, with most of the cases being in patients aged > 5 years. In a recent study of both outpatients and inpatients ≥ 1 year of age with AFI in Tanzania, influenza A was detected in 24% and HRV was detected in 25%.21 In our study, the overall prevalence of respiratory viral infection at 20% was generally higher than that previously reported, which may be secondary to a substantial proportion of our cohort consisting of children. More than half of the children aged < 5 years in our cohort had respiratory virus identified, although up to 20% of patients in other age groups also tested positive for respiratory viruses. The burden of respiratory viral disease may be underappreciated in settings where testing is limited because clinical judgment alone may not suffice for differentiating between illnesses. For example, influenza A has previously been shown to present with hemorrhagic manifestations and thrombocytopenia, and may be confused with other illnesses such as dengue or leptospirosis.22,23

In Sri Lanka, limited prior studies have identified the epidemiology of respiratory viral infection, and all of these studies have focused on pediatric populations. Among children aged ≤ 5 years hospitalized with respiratory illness in the Central and North Central provinces, > 40% had respiratory viruses detected, with RSV being most common and PIV, adenovirus, influenza, and hMPV also being present.24 Among children aged ≤ 3 years hospitalized with respiratory illness in the Sabaragamuwa Province, 32% had respiratory virus, with 90% being RSV and the remainder being PIV and influenza.25 Interestingly, in our study in the southern province, influenza was the most common respiratory virus identified, even among children aged < 5 years. This finding is likely because of our cohort including patients with AFI rather than solely respiratory illness. By performing surveillance over a 2-year period and including a large cohort of both children and adults, we were able to obtain a relatively comprehensive picture of the epidemiology of respiratory viral disease in this region. The World Health Organization (WHO) has highlighted the need for greater knowledge and interventions on viral respiratory diseases to reduce morbidity and mortality by initiating the Battle against Respiratory Viruses agenda.26 Among other measures, this initiative recommends improving global surveillance for respiratory viruses and improving understanding of the geographical patterns, seasonality, and distribution of respiratory viruses.26

In our study, both influenza A and respiratory viral activity peaked in February–June of 2013–2014. We have previously shown that among outpatients presenting with influenza-like illness in the Southern Province, influenza and respiratory viral activity peaked in March–June of 2013–2014, substantiating our present findings from the inpatient setting.27 In tropical and subtropical countries such as Sri Lanka, studies have shown that the seasonality of respiratory viruses varies widely and may be impacted by local variations in temperature, humidity, and rainfall.28,29 Thus, even within a country, respiratory viral seasonality may fluctuate, and understanding local epidemiology is important for targeting preventative health measures.30 Presently, less than 1% of the Sri Lankan population receives influenza vaccination and there is no national vaccination policy.31 Using data available through the WHO’s FluNet from 2010 to 2015 and national surveillance data available from 2000 to 2014 (excluding 2009–2010), Hirve et al.12 found that the primary influenza peak in Sri Lanka occurred in October–December, with a lesser peak in January–March. Hirve et al. recommended that the Northern Hemisphere vaccine formulation (available annually in October) be used in Sri Lanka, with targeted vaccination from October to December. However, our findings suggest that in the Southern Province of Sri Lanka, peak influenza activity is in February–June, and that the Southern Hemisphere formulation (available annually in April) may be important in providing protection. Enhanced local surveillance, typing of influenza strains, and correlation with vaccine formulation may help determine the best strategy for vaccine deployment in the country in the future.

Respiratory viral activity was associated with warmer temperatures in our study, which is contrary to the pattern generally seen in temperate regions.32 Associations of respiratory viral activity with temperature are often not observed in tropical and subtropical settings, and of meteorological parameters, relative humidity is most often correlated with respiratory viral activity in the literature.3335 As with seasonality, associations between meteorological parameters and respiratory viral activity may vary by subregion within a country in tropical and subtropical settings.

Patients with respiratory viruses generally had lower severity of illness than other patients in our AFI cohort, with shorter durations of fever and hospitalization. Diagnoses such as dengue, leptospirosis, and enteric fever in the remainder of the cohort may account for such differences because these illnesses are traditionally associated with longer illness. The symptom of cough with non-respiratory illnesses such as dengue has been documented in other studies, and was present in more than a third of our patients who did not have a respiratory viral infection.36 The duration of cough may be an important feature in helping a clinician to distinguish between respiratory viral versus other etiologies of AFI because patients with respiratory viruses generally had 7 days of cough or less in our study. This finding is in keeping with surveillance definitions for influenza-like illness, which limit cough duration to 7–10 days.37,38

Patients with respiratory viral infection were as likely as other patients to receive chest X-rays and to have abnormalities on chest X-ray. However, more than 50% of patients who had respiratory virus identified were treated with antibiotics at enrollment. This group represents an important population that should be targeted for improved antimicrobial stewardship efforts. We have previously demonstrated that almost 80% of outpatients with respiratory viral illnesses in Sri Lanka receive antibiotic prescriptions.39 Given the current global crisis in antimicrobial resistance, rapid and multiplex diagnostics that identify respiratory viruses may help reduce antimicrobial overuse in this and other settings.40,41 However, the cost and availability of such diagnostics may continue to be a barrier to access, and cost-effectiveness studies remain scarce.42

Some limitations should be noted. The identification of respiratory virus from the nares or nasopharynx may represent passive colonization rather than infection, and we did not have an age-matched cohort without infectious symptoms as a control group. However, most patients with respiratory virus identified (> 80%) had respiratory symptoms, and prior studies suggest that the isolation of influenza, which was the most commonly identified virus in our study, correlates with infection rather than colonization.21,43 We only recorded antibiotic use at enrollment and at hospital discharge, and did not track antiviral use during hospitalization. Assessment of antimicrobial use throughout the course of hospitalization may help better identify targets for future antimicrobial stewardship efforts. Finally, our cohort consisted of patients with acute undifferentiated febrile illness; patients who did not develop a fever or patients who had a focal pneumonia identified on examination or chest X-ray would thus have been excluded from this analysis.

In conclusion, respiratory viruses were a common and under-recognized cause of illness among patients hospitalized with AFI in southern Sri Lanka. An improved understanding of the burden and seasonality of respiratory viruses may help inform preventative and clinical decisions such as vaccination and the use of antimicrobials.

Acknowledgments:

We thank the research and laboratory staff who helped conduct this study.

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Author Notes

Address correspondence to L. Gayani Tillekeratne, Duke Global Health Institute, 310 Trent Dr., Durham, NC 27705. E-mail: gayani.tillekeratne@dm.duke.edu

Please note that Megan E. Reller and Christopher W. Woods are co-senior authors.

Conflicts of Interest: Dr. Woods reports other relationships with Predigen; personal fees from IDbyDNA, Becton Dickinson, and Giner; grants and personal fees from bioMerieux; and grants from Pfizer, Biofire, Openbiome, Janus, BioMeme, MRI Global, and RTI, outside the submitted work.

Financial support: This work was supported by a grant from the National Institutes of Allergy and Infectious Diseases (K23AI125677 to LGT); Fogarty International Center and the National Institute of Mental Health (#R25 TW009337), the U.S. Department of Defense (BA150703 to CWW); the Office of Naval Research to the Emerging Infectious Diseases Programme, Duke-NUS Graduate Medical School, Singapore; a Johns Hopkins Center for Global Health Junior Faculty Grant (MER); and the Hubert-Yeargan Center for Global Health.

Authors’ addresses: L. Gayani Tillekeratne, Truls Østybe, Megan E. Reller, and Christopher W. Woods, Duke University, Durham, NC, Duke Global Health Institute, Durham, NC, and Duke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka, E-mails: gayani.tillekeratne@dm.duke.edu, truls.ostbye@duke.edu, megan.reller@duke.edu, and chris.woods@duke.edu. Champica K. Bodinayake, Ajith Nagahawatte, and Vasantha Devasiri, Duke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka, and Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka, E-mails: bodinayake@gmail.com, ajithnagahawatte@yahoo.co.uk, and vdevasiri@gmail.com. Ryan Simmons, Duke Global Health Institute, Durham, NC, E-mail: ryan.simmons@duke.edu. Wasantha Kodikara Arachchi, Duke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka, and Teaching Hospital Karapitiya, Galle, Sri Lanka, E-mail: kody@sltnet.lk. Bradly P. Nicholson and Sky Vanderburg, Duke University, Durham, NC, and Duke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka, E-mails: brad.nicholson@duke.edu and sky.vanderburg@duke.edu. Larry P. Park, Duke University, Durham, NC, and Duke Global Health Institute, Durham, NC, E-mail: larry.park@duke.edu. Ruvini Kurukulasooriya, Duke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka, E-mail: ruhunasearch@gmail.com. Aruna Dharshan De Silva, Duke-Ruhuna Collaborative Research Centre, Galle, Sri Lanka, and General Sir Kotelawala Defence University, Ratmalana, Sri Lanka, E-mail: dslv90@yahoo.com.

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