|Year : 2017 | Volume
| Issue : 1 | Page : 9-13
Risk factors for death during a resurgence of influenza-A (H1N1) pdm09 in Punjab State in 2013
Tripurari Kumar1, Deepak Bhatia2, Pinnaka Venkata Maha Lakshmi3, Kayla F Laserson4, Jai Prakash Narain5, Rajesh Kumar6
1 EIS Officer, Central Surveillance Unit, Integrated Disease Surveillance Program, National Centre for Disease Control, New Delhi, India
2 State Surveillance Officer, State Surveillance Unit, Integrated Disease Surveillance Program, Director Health Services, Chandigarh, India
3 Additional Professor of Epidemiology and Professor and Head, School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, India
4 Country Director, Center for Global Health, Centers for Disease Control and Prevention (CDC), India-CDC, New Delhi, India
5 Senior Advisor, EIS Programme, National Centre for Disease Control, Delhi, India
6 Professor and Head, School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, India
|Date of Web Publication||16-Feb-2017|
Department of Community Medicine and School of Public Health, Postgraduate Institute of Medical Education and Research, Chandigarh
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: In 2013, high mortality from influenza-A (H1N1) pdm09 (pH1N1) was observed in Punjab, India. Objectives: To describe cases and deaths of 2013 pH1N1 positives, to evaluate the high case fatality ratio and risk factors for pH1N1-associated mortality among the hospitalized cases in Punjab for 2013. Methods: A case–control study was conducted and compared those who died from confirmed pH1N1 with those who survived in the hospital between January 1, 2013, and April 30, 2013. Sociodemographic and clinical details were extracted from hospital records and from telephone interviews with controls and next of kin of cases using pretested questionnaires. Logistic regression analysis was performed. Results: A total of 182 laboratory-confirmed pH1N1 cases (99 males and 83 females) were hospitalized in 30 hospitals in Punjab; 42 (23%) patients died. Those who died were significantly more likely to be younger than 50 years of age (adjusted odds ratio [AOR] =10.6, 95% confidence interval [CI] =1.8–21.1), be obese (AOR = 16.7, 95% CI = 1.6–170.7), and have visited more than two health-care facilities before laboratory confirmation (AOR = 25.8, 95% CI = 5.4–121.6). Conclusions: The health-care community should have a high index of suspicion for influenza, and general community should be sensitized about risk factors and to seek medical advice early in the illness.
Keywords: Body mass index, India, influenza-A pH1N1, Integrated Disease Surveillance Program, mortality, Punjab
|How to cite this article:|
Kumar T, Bhatia D, Maha Lakshmi PV, Laserson KF, Narain JP, Kumar R. Risk factors for death during a resurgence of influenza-A (H1N1) pdm09 in Punjab State in 2013. Indian J Public Health 2017;61:9-13
|How to cite this URL:|
Kumar T, Bhatia D, Maha Lakshmi PV, Laserson KF, Narain JP, Kumar R. Risk factors for death during a resurgence of influenza-A (H1N1) pdm09 in Punjab State in 2013. Indian J Public Health [serial online] 2017 [cited 2022 Jan 19];61:9-13. Available from: https://www.ijph.in/text.asp?2017/61/1/9/200246
| Introduction|| |
Influenza viruses undergo frequent genetic changes that lead to epidemics and occasionally to pandemics. Each century has seen some pandemics rapidly progressing to all parts of the world due to emergence of a novel virus to which the overall population holds no immunity. Globally, 250–500,000 deaths from influenza occur each year, with an estimated 3–5 million severe cases annually. In addition, influenza causes substantial economic impact from direct health-care costs, societal costs, and other trade-related loses; data available from the USA suggest that influenza costs approximately 87.1 billion dollars every year. However, data on the impact of influenza in India are limited. In April 2009, a novel influenza virus known as influenza A (H1N1) pdm09 (pH1N1) virus was first identified and rapidly spread globally resulting in an influenza pandemic. The pandemic outbreak of 2009 occurred late in the season  and appeared to affect young people disproportionately. Most cases of severe and fatal infection occurred in adults between the ages of 30 and 50 years. The pandemic caused widespread social disruptions around the world. On June 14, 2009, the first case in Punjab, India, was in a group of students returning from the United States. Seven students from the city of Jalandhar, Punjab, tested positive for pH1N1. In Punjab, the total number of cases reported in 2010, 2011, and 2012 was 77, 25, and 15, respectively, and resurgence occurred in January 2013. From January 1, 2013, to April 30, 2013, there were 183 positive hospitalized cases reported in Punjab, of whom 42 died (case fatality ratio [CFR] =21.8%).
The objectives of the study were to describe cases and deaths of 2013 pH1N1 positives and to evaluate the high CFR and risk factors for pH1N1-associated mortality among the hospitalized cases in Punjab for 2013.
| Materials and Methods|| |
Punjab state is situated in the northwest part of India. It occupies 1.6% of the geographic area and 2.3% of India's population (27.7 million). Surveillance of influenza A (H1N1) in Punjab is conducted by the Integrated Disease Surveillance Programme (IDSP). Nasal or throat swabs from all severe acute respiratory infections' (SARIs) cases from both public and private health facilities (n = 30) were sent to the designated virology laboratory at the Postgraduate Institute of Medical Education and Research, Chandigarh, for laboratory confirmation of pH1N1 infection, using real-time reverse transcriptase polymerase chain reaction (rT-PCR) by the district surveillance units under IDSP. SARI surveillance is the only source of identification of pH1N1 infections in India including Punjab. Laboratory-confirmed patients were notified to the district and state IDSP. The district IDSP provided complete treatment to positive cases and close contacts with approved influenza antiviral drugs and collected clinical data on any death. The government provided antiviral drugs for free of cost at each district hospital and not below district level health-care settings such as Primary Health Centers or Community Health Centers.
The cases of pH1N1 were defined using the SARI case definition, i.e., as a hospitalized patient with high-grade fever (≥38°C) and cough/sore throat, worsening chronic conditions or in a high-risk group with laboratory-confirmed pH1N1 influenza A virus detected by rT-PCR, occurring from January 1, 2013, to April 30, 2013, in Punjab. High-risk groups include children under 2 years of age, adults more than 65 years, pregnant and postpartum women, and chronic conditions being people with chronic pulmonary and cardiovascular and those with neurologic and immunosuppressant disorders.
The pH1N1 cases and deaths were described and a case–control study was conducted. For the case–control study, all deaths were selected and then selected controls only from those hospitals where deaths due to pH1N1 had also occurred between January 1, 2013 and April 30, 2013 (21/31 hospitals). A sample size of 41 cases and 82 controls was required to estimate an odds ratio (OR) of 3 with 95% confidence and 80% power assuming 30% of the controls had exposures such as obesity, pregnancy, and comorbid illnesses.
The sociodemographic data collected included age, sex, place of residence (rural or urban), and education status of the patients. Data on comorbidities such as obesity, diabetes, hypertension, heart disease, liver disorder, concurrent respiratory illness such as chronic obstructive pulmonary disease/tuberculosis, and pregnancy status if female were extracted from the clinical records. Obesity was defined as body mass index (weight/height 2) >30 kg/m 2. The study participants or their next of kin were contacted to obtain missing data. The delay in treatment, defined at ≥2 days from symptom onset to treatment initiation, was also considered as a risk factor for mortality because the effectiveness of the oseltamivir treatment depends on the time of treatment initiation following onset of symptoms.
Data were entered in Epi Info 7 (Atlanta, GA, USA) software for analysis. Bivariate and multivariate analysis was performed to calculate ORs, adjusted OR (AOR), and 95% confidence interval (CI) for risk factors associated with pH1N1 mortality. For the multivariate logistic regression, a backward elimination modeling strategy was used and evaluated all variables which were statistically significant (P < 0.05) in bivariate analysis. Independent variables were age and religion and dependent variables were obesity, patient on ventilator, and visit to >2 centers before pH1N1 confirmation.
Confidentiality of all patients was maintained by assigning a unique identifier for each patient. Oral consent was obtained before start of the telephonic interview of controls and next of kin's of the cases. The permission from health authorities in Punjab was obtained to review medical and death records of study participants.
| Results|| |
From January 1, 2013 to April 30, 2013, there were 559 SARI cases tested for pH1N1 in all of Punjab; 182 (33%) were found positive. The median age of the pH1N1 cases was 46 years (interquartile range = 40–54 years). More than half of the cases (52.7%) were 15–49 years and 54.1% (n = 99) were males. Twenty-three percent (42/182) hospitalized pH1N1 cases died. All 22 districts of Punjab reported that pH1N1 cases and cases were reported from urban as well as rural areas. The Southeastern part of Punjab reported a higher prevalence, in particular Mohali, Fatehgarh Sahib, and Bathinda districts [Figure 1]. There was no history of travel or history of prior vaccination against pH1N1 found among cases. The first case was reported on January 1, 2013, and cases started increasing from the 1st week of January, peaked in mid-February, and then declined by the end of March [Figure 2].
|Figure 1: Prevalence of pH1N1 Cases in Punjab, January 1, 2013–April 30, 2013.|
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|Figure 2: Distribution of pH1N1 Hospitalizations and deaths by date of onset, Punjab, January–April, 2013.|
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Of 182 cases, 163 pH1N1 patients came from the 21 hospitals where the 42 deaths occurred. These 42 deaths were considered as cases, and 80 of the 121 remaining patients whose survival status was known and medical records were available were enrolled as controls for the case–control study [Figure 3]. The 27 patients for whom records were not available were significantly younger (<50 years) than those whose records were available (OR = 5.7, 95% CI = 1.8–18.1), but there was no significant difference by sex (OR = 1.2, 95% CI = 0.5–2.8).
On bivariate analysis, comparison of sociodemographic characteristics of cases versus controls revealed that cases were almost three times more likely to be younger than 50 years old than controls (OR = 2.8, 95% CI = 1.2–6.4) [Table 1]. Cases were ten times more likely to be obese than controls (OR = 10.2, 95% CI = 2.7–39). Other comorbid conditions such as history of diabetes, cardiovascular disease, liver disorder, blood disorder and kidney disorders, or being pregnant were not significantly associated with pH1N1 mortality. The delays in oseltamivir treatment initiation between cases and controls were compared. No cases and only one control started treatment within 48 h and less than a one-third of both cases (29%) and controls (24%) started treatment within 1 week. Cases were over thirty times more likely than controls to visit more than two places before receiving an pH1N1 diagnosis (OR = 31.7, 95% CI = 9.5–105.4). These patients also received antiviral treatment more than 48 h after onset of symptoms. Multivariate logistic regression revealed that age <50 years (AOR = 10.1, 95% CI = 1.1–21.1), obesity (AOR = 16.7, 95% CI = 1.6–170.7), and referral to more than two centers before diagnosis (AOR = 25.8, 95% CI = 5.4–121.6) remained independently associated with mortality even after controlling for disease severity, that is, ventilator support (AOR = 51.5, 95% CI = 7.3–363.1) [Table 2].
|Table 1: Characteristics of cases (died) and controls (survived) among those with severe acute respiratory illness and influenza A (pH1N1) pdm09 infection, Punjab, January-April 2013|
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|Table 2: Logistic regression model of independent factors associated with mortality|
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| Discussion|| |
High pH1N1 mortality in Punjab in 2013 was observed. A history of obesity, age <50 years, and delays in hospitalization were independent predictors of mortality. Most of the affected individuals were aged between 15 and 49 years and 23% of the laboratory-confirmed patients died. Our study is the first study in Punjab to document this specific age distribution of influenza cases and a death to hospitalization rate of >20%.
Most of the cases caused by the influenza A (pH1N1) virus have been mild and self-limiting in nature. Influenza A (pH1N1) has a higher risk of adverse outcome among those with diabetes mellitus, hypertension, cardiac disease, chronic respiratory disease, HIV infection (immune compromised), and pregnant women. Studies have also shown that those who are obese,, those who delay in initiating treatment,, and younger patients  are at higher risk for worse outcomes with influenza A (pH1N1). Sixty-one percent of the pH1N1 cases who died and 46% of the pH1N1 cases who had recovered in this evaluation had at least one of these risk factors. The presence of one or more risk factors increases the severity of disease and alters the prognosis of patients who ultimately require intensive care and ventilator support.
Treatment with a neuraminidase inhibitor is especially important for influenza patients with underlying risk factors, including pregnancy, and those with severe or progressive clinical illness. Early therapy within 48 h of onset with oseltamivir has also been found to reduce the duration of hospitalization and the risk of progression to severe disease requiring Intensive Care Unit admission or risk of death., In Punjab, all pH1N1-positive cases were given influenza antiviral drugs irrespective of the severity of illness, but it was found that such therapy was started only after 48 h in the majority of cases. Those patients, who had delayed initiation of treatment, also visited more than two health facilities. The statistically significant association between visiting ≥2 health facilities before laboratory confirmation and death also indicated delays in care led to delayed start of antiviral treatment. Oseltamivir is readily available at the district hospitals and selected private hospitals. Patients either did not get medication because of low awareness among health providers below the district level or reported late due to reluctance/barriers to getting to facilities before the onset of severe symptoms. Further study is needed to explore the exact cause of delays of oseltamivir treatment. In India, other studies also had reported late presentations to health-care facilities. Treatment was delayed in some patients even after reporting to their physicians. The reason for this could be that pH1N1 was not suspected or considered for differential diagnosis. Physicians may start antipyretics and antibiotics for the common cold and wait for response, which may delay appropriate treatment.
This study had several limitations. First, the study was conducted among hospitalized laboratory-confirmed cases only. It is possible that additional cases did not access the hospital or get tested in the laboratory due to logistic or transport issues of getting the specimen to the laboratory. It is also likely that many cases were not severe enough to require medical care. Second, those controls whose medical records were not available were excluded from the study. These excluded cases were significantly younger than the rest of the controls, and hence, there is a possibility of bias affecting the study as age was one of the significant risk factors for mortality due to pH1N1 infection. Third, there could be recall bias from controls and next of kin for cases, which might have overestimated or underestimated the presence of potential risk factors and also there may have been a bias in detection of more severe hospitalized cases resulting in an overestimate of the proportion of hospitalization that resulted in death. Finally, because of the study design, hospital could not be evaluated as a risk factor.
| Conclusion|| |
There were an increased number of hospitalized cases of pH1N1 with a high case fatality in Punjab in 2013. All districts were affected with no clusters seen. The most affected ages were those 15–49 years. Age <50 years and delays in accessing the appropriate diagnosis and treatment initiation were significantly associated with an adverse outcome. Obesity was an additional risk factor for death.
As the delay in accessing care due to visits >2 centers before pPH1N1 confirmation was found to be a significant risk factor of mortality among hospitalized pH1N1 cases, It is recommended that community and health care providers should be sensitized for early referral to individuals who are having SARI with obesity to appropriate health care facilities where testing and treatment facilities are available for pH1N1. Surveillance activities should be strengthened by increasing laboratory testing facilities in the state and collecting additional information such as disease severity and comorbidity for all cases.
The authors would like to thank the India EIS Programme, the National Centre for Disease Control and acknowledge everyone especially to the Integrated Disease Surveillance Programme, Punjab team, Medical Superintendents of government and private hospitals of Punjab who helped and supported to conduct this study, and also Postgraduate Institute of Medical Education and Research, Chandigarh, for laboratory support to test pH1N1 cases in Punjab.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2]
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