Abstract
Objective
To describe household‐level risk factors for secondary influenza‐like illness (ILI), an important public health concern in the low‐income population of Bangladesh.
Methods
Secondary analysis of control participants in a randomised controlled trial evaluating the effect of handwashing to prevent household ILI transmission. We recruited index‐case patients with ILI – fever (<5 years); fever, cough or sore throat (≥5 years) – from health facilities, collected information on household factors and conducted syndromic surveillance among household contacts for 10 days after resolution of index‐case patients’ symptoms. We evaluated the associations between household factors at baseline and secondary ILI among household contacts using negative binomial regression, accounting for clustering by household.
Results
Our sample was 1491 household contacts of 184 index‐case patients. Seventy‐one percentage reported that smoking occurred in their home, 27% shared a latrine with one other household and 36% shared a latrine with >1 other household. A total of 114 household contacts (7.6%) had symptoms of ILI during follow‐up. Smoking in the home (RR adj 1.9, 95% CI: 1.2, 3.0) and sharing a latrine with one household (RR adj 2.1, 95% CI: 1.2, 3.6) or >1 household (RR adj 3.1, 95% CI: 1.8–5.2) were independently associated with increased risk of secondary ILI.
Conclusion
Tobacco use in homes could increase respiratory illness in Bangladesh. The mechanism between use of shared latrines and household ILI transmission is not clear. It is possible that respiratory pathogens could be transmitted through faecal contact or contaminated fomites in shared latrines.
Keywords: influenza, Bangladesh, sanitation, environmental tobacco smoke, air pollution, respiratory infections
Abstract
Objectif
Décrire les facteurs de risque au niveau des ménages pour les maladies de type grippal (MTG) secondaires, un problème important de santé publique dans la population à faible revenu du Bangladesh.
Méthodes
Analyse secondaire des participants témoins dans un essai contrôlé randomisé évaluant l'effet du lavage des mains pour éviter la transmission de MTG dans les ménages. Nous avons recruté des patients (cas indices) atteints de MTG ‐ fièvre (<5 ans); fièvre, toux ou mal de gorge (≥5 ans) – dans les services de santé, avons colleté des informations sur les facteurs au niveau du ménage et avons mené une surveillance syndromique chez les contacts dans le ménage pendant 10 jours après la résolution des symptômes des patients indices. Nous avons évalué les associations entre les facteurs du ménage à la ligne de base et les MTG secondaires chez les contacts dans le ménage en utilisant la régression binomiale négative, en tenant compte du regroupement par ménage.
Résultats
Notre échantillon était constitué de 1491 contacts de ménage de 184 patients indices. 71% ont déclaré que du tabac était fumé chez eux, 27% partageaient une latrine avec un autre ménage et 36% partageaient une latrine avec plus d'un ménage. Au total, 114 contacts de ménage (7.6%) avaient des symptômes de MTG pendant le suivi. Le fait de fumer dans le domicile (RR adj: 1.9; IC95%: 1.2–3.0) et le partage de latrines avec 1 ménage (RR adj: 2.1; IC95%: 1.2–3.6) ou avec plus d'un ménage (RR adj: 3.1; IC95%: 1.8–5.2) étaient indépendamment associés à un risque accru de MTG secondaires.
Conclusion
L'usage du tabac dans les ménages pourrait augmenter les maladies respiratoires au Bangladesh. Le mécanisme entre l'utilisation partagée de latrines et la transmission des MTG dans les ménages n'est pas clair. Il est possible que des pathogènes respiratoires puissent être transmis par contact fécal ou par des fomites contaminés dans des latrines partagées.
Mots‐clés
Influenza, Bangladesh, sanitaire, fumée de tabac ambiante, pollution de l'air, infections respiratoires.
Abstract
Objetivo
Describir los factores de riesgo en el hogar para enfermedades secundarias tipo influenza (ETI), una preocupación importante en salud pública, entre la población con ingresos bajos en Bangladesh.
Métodos
Análisis secundario de control de participantes en un ensayo aleatorizado y controlado que evalúa el efecto del lavado de manos para prevenir la transmisión de ETI en hogares. Hemos reclutado pacientes primarios con fiebre por ETI (<5 años); fiebre, tos o dolor de garganta (≥5 años) en los centros sanitarios, recogido información sobre los factores del hogar, y realizado una vigilancia sindrómica entre los contactos del hogar hasta 10 días después de la resolución de los síntomas del caso primario. Hemos evaluado las asociaciones entre los factores del hogar al inicio y los ETI secundarios entre los contactos del hogar, mediante una regresión binomial negativa, teniendo en cuenta los conglomerados por hogar.
Resultados
Nuestra muestra era de 1491 contactos pertenecientes a los hogares de 184 pacientes primarios. Un 71% reportaron que en su hogar se fumaba, un 27% compartían letrina con 1 otro hogar y un 36% compartían una letrina con >1 hogar. Un total de 114 contactos de los hogares (7.6%) presentaron síntomas de ETI durante el seguimiento. Fumar en el hogar (RR adj 1.9, IC 95% 1.2, 3.0) y compartir la letrina con 1 hogar (RR adj 2.1, IC 95% 1.2, 3.6) o >1 hogar (RR adj 3.1, IC 95% 1.8‐5.2) estaban independientemente asociados con un riesgo aumentado de ETI secundaria.
Conclusión
El consumo de tabaco en los hogares podría aumentar la enfermedad respiratoria en Bangladesh. El mecanismo existente entre uso de letrinas compartidas y la transmisión de ETI en los hogares no queda claro. Es posible que los patógenos respiratorios puedan transmitirse mediante contacto fecal o fómites contaminados en letrinas compartidas.
Palabras clave
Influenza; Bangladesh; sanidad; humo de tabaco ambiental; polución del aire; infecciones respiratorias
Introduction
Annual influenza epidemics occur worldwide with sporadic pandemics. Influenza is an important aetiological agent for febrile illness and pneumonia among children in urban Dhaka, Bangladesh 1, 2, 3, where influenza incidence is approximately 100 episodes per 1000 child‐years, and an estimated 10% of childhood pneumonia episodes are influenza‐associated 2. Influenza‐like illness (ILI) refers to a syndrome with symptoms typical of influenza virus infection: fever with sore throat and/or cough 4. In community‐based surveillance in Bangladesh, 14% of all people who died during 2009, excluding those who died from injury, suicide or homicide, had symptoms of ILI within 14 days before death 5. Although 2009 was a pandemic year, which may have influenced mortality from influenza, hospital‐based surveillance indicates a similar incidence of influenza‐associated ILI in 2008 (10 cases per 100 person‐years), 2009 (6.6 cases of seasonal influenza and 4.4 cases of pandemic influenza per 100 person‐years) and 2010 (17 cases per 100 person‐years) 3.
In Bangladesh, influenza and ILI result in a high economic burden for families of ill individuals. Families of individuals with influenza identified during surveillance paid a median of 16% of monthly household income in out‐of‐pocket costs for treatment of influenza‐associated illness 6. Many families reported reducing monthly food expenditures and/or borrowing money in order to pay for treatment 6, 7. Ill individuals may be unable to work and/or attend school for several days, further increasing the financial burden on families 6, 7.
Annual vaccination is a key strategy for the prevention of influenza in high‐ and middle‐income countries 8. In Bangladesh, as in many low‐income countries, vaccination against influenza viruses has not been widely promoted, likely due to high costs and competing priorities of the healthcare system 9. Non‐pharmaceutical interventions that modify influenza transmission risk factors would be particularly useful in such a setting.
Respiratory virus transmission has been demonstrated in Hong Kong and the United States to be common among household contacts 10, 11. Household contacts are in frequent contact with infected individuals and have similar risk factors to infected household members 10, 11. Crowding and poor hand hygiene, which are prevalent in low‐income settings, facilitate transmission of influenza and other respiratory viruses 12, 13, 14, 15. Handwashing has been associated with a reduced risk of acute respiratory infections in children 13, 16 and influenza transmission 11, 17 in high‐ and low‐income settings. Exposure to indoor and ambient air pollution has been associated with an increased risk of all‐cause acute respiratory infections 18, 19, 20, 21. Exposure to air pollution may damage lung tissue and compromise immunity, increasing susceptibility to respiratory infection 22, 23. Air pollution concentrations in a home can be affected by tobacco smoking, biomass fuel use for cooking and proximity to biomass cookstoves 24, 25.
Influenza and ILI carry a high disease burden and subsequent economic burden in Bangladesh, a lower middle‐income country where widespread pharmaceutical interventions may not be currently feasible or affordable for patients. However, most studies on non‐pharmaceutical interventions for influenza have been conducted in high‐income settings. It is, therefore, important to identify and address modifiable factors associated with secondary ILI, defined as ILI in another household compound member after the first patient has been identified, at the household level in Bangladesh and other high‐burden, low‐income settings in order to design interventions to reduce transmission. For this study, we aimed to identify household‐level risk factors associated with secondary ILI in rural Bangladesh.
Methods
Study population
We conducted this analysis using the control group of a randomised controlled trial, Bangladesh Interruption of Secondary Transmission of Influenza Study (BISTIS) 26. During the 2009 and 2010 influenza seasons, patients who sought care for respiratory symptoms at Jahurul Islam Medical College Hospital, two district health complexes, and six local pharmacies in rural Kishoreganj District, Bangladesh, were recruited as index‐case patients. Study physicians screened patients for the presence of influenza‐like illness (ILI), which was defined as fever in those less than 5 years of age and fever with cough or sore throat in those 5 years or older. As this study was investigating transmission of influenza at the household level, patients who were admitted to the hospital were ineligible to participate. Consenting index‐case patients were accompanied to their home by study staff. Typically, residents of this area live with extended family members in compounds of several households, sometimes with a shared cooking space and a latrine. If at least two people other than the index‐case patient intended to reside in the compound for the subsequent 20 days, we sought to enumerate and enrol all members of the compound (Figure 1).
Figure 1.
Schematic of participant selection for secondary analysis of household‐level risk factors for influenza‐like illness transmission. This analysis was limited to participants in the control arm.
Eligibility requirements
Eligibility requirements of index‐case patients varied during the study period 26. Briefly, in 2009, we recruited index‐case patients who experienced symptom onset in the prior 7 days, who lived within 30 min travel time to the health facility, and had no ILI among household compound members in the prior 3 days (n = 18). Due to a lack of recruitment, after one month, we expanded this criteria to include those living within two hours’ travel time and those with ILI in other household compound members (n = 65). In 2010, in response to literature indicating that handwashing was effective against influenza transmission within 36 h of symptom onset 11, we limited enrolment to index‐case patients with symptom onset within 48 h. We allowed recruitment of those compounds where individuals who did not live in the index‐case patient's home had ILI (n = 103). Full details of the eligibility requirements are described elsewhere 26. Household contacts who had fever at enrolment (n = 53) were excluded from these analyses.
Randomisation to an intensive handwashing intervention or control arm was carried out at the compound level. Details of the handwashing intervention are described elsewhere 26. The following analyses were conducted among participants randomised to the control group to reflect household‐level risk factors for ILI.
Data collection and laboratory testing
At the initial healthcare facility visit of the index‐case patient, a trained study physician procured specimens using a nasal swab and an oropharyngeal swab, which were batched and tested by RT‐PCR for influenza viral RNA using the World Health Organization protocol 27. After index‐case patients were recruited and tested for influenza virus infection, study staff accompanied index‐case patients to their homes and recruited members of their compounds into the study. A staff member then administered a questionnaire to the male or female head of each household in the compound to assess demographics, socio‐economic factors and individual‐ and household‐level characteristics. The staff member observed each household for certain factors such as presence of a handwashing station with soap and water, location of cooking area, type of fuel used, water source and latrine facilities.
Study staff visited each household compound daily until the tenth day after resolution of the index‐case patient's symptoms to conduct surveillance for ILI symptoms. Any member of the compound with new ILI symptoms during the follow‐up period was considered a secondary ILI case. After consent was obtained, the secondary ILI case patients were tested for influenza in the same manner as the index‐case patient.
Written informed consent for specimen collection was obtained from all adult index‐case patients and secondary ILI cases. If the index‐case patient or secondary ILI case was a child, written informed consent for specimen collection was obtained from a parent or guardian. Written informed consent was obtained from the head of the compound (typically the eldest male) for all household data collection activities. All study procedures were approved by the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) Research and Ethics Review Committees.
Data analysis
As few (n = 35) index‐case patients had laboratory‐confirmed influenza in the control arm, we included all index‐case patients with ILI and conducted analyses to determine household‐level risk factors associated with secondary ILI in household members. We examined the following household‐level characteristics as potential risk factors for secondary ILI: crowding, building materials of homes, exposure to indoor air pollution, presence of handwashing materials, water source, latrine quality and sharing, education of the household respondent and household wealth status. Crowding was assessed as number of people per room (the number of people in the household divided by the number of rooms in the home, excluding latrine and kitchen). We assessed indicators of exposure to indoor air pollution, such as frequency of smoking in the home, cooking fuel use, building material of the home and the distance between the cooking and sleeping spaces. We observed handwashing materials, soap and/or water at a handwashing station 28. We defined latrine quality as improved (flush/pour flush to piped sewer system, septic tank or pit latrine; or pit latrine with slab) or unimproved (flush/pour flush to elsewhere, open pit latrine, bucket, hanging latrine or no facility/bush/field), according to the WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation. For socio‐economic status, we examined education level of the household respondent and developed a wealth index using principal component analysis of household assets 29. We used the first principal component as our wealth index and categorised it into quintiles. We also examined each household asset that weighed on the wealth index in principal components analysis as indicators of wealth.
We reported household‐level factors potentially associated with ILI transmission at the household and individual levels. Those factors with 10–90% variability among all households were considered for multivariable analysis. We adjusted multivariable models for age of the index‐case patient (<5 years, ≥5 years), as previous analyses showed age to be associated with ILI transmission in BISTIS 26. We examined age of the susceptible contact as a potential confounder, both as a continuous variable and defined in the following categories: very young child (less than 2 years), young child (2–4 years), older child (5–14 years), adult (15–49 years) and older adult (50 years and older). We examined sex and wealth status of the susceptible household contact, as well as any factors associated with risk of ILI in the bivariate models (P < 0.05) as potential confounders. Since case definition varied by age, we conducted a sensitivity analysis in which we stratified analyses by age of the index‐case patient (<5 years, ≥5 years). We also examined bivariate associations between household factors associated with secondary ILI and multiple daily interactions with the index‐case patient (collected in 2010), as this was shown in our prior study to be associated with ILI 26.
We conducted mixed‐effects log‐binomial regression to evaluate the relationship between household‐level factors and identification of a secondary case of ILI, adjusting for age of the index‐case patient and the susceptible household contact, and we accounted for clustering at the household level. In order to evaluate independent associations, we adjusted models for all other household‐level factors associated with secondary ILI in bivariate analyses (P < 0.05). We estimated the adjusted risk ratios of developing a secondary ILI case among those who lived in households with factors of interest compared with those who lived in households without the factors of interest.
Results
Among 1498 susceptible household contacts of 184 index‐case patients, seven individuals (0.5%) from two households were excluded due to missing data. A total of 114 (7.6%) susceptible contacts developed ILI symptoms during follow‐up. Among 1491 household contacts included in this analysis, 722 household members were from 181 index‐case patient households and 769 from 182 households in the compound other than the index‐case patient's household (Table 1). Houses typically consisted of one (50%) or two (30%) rooms, were made of brick or concrete (77%) and had a separate cooking space outside of the main living area (86%). Almost all households cooked with biomass fuels and used tube wells for drinking water. Smoking occurred in approximately 69% of homes. Of 1491 household contacts, 207 (14%) reported smoking; 197 (29%) of adult men were smokers vs. 10 (1.3%) of adult women (results not shown). Most (83%) household respondents had eight or fewer years of education. Our wealth index accounted for 31% of the variance in asset ownership. A total of 46 (40%) of the 114 secondary ILI cases lived in the index‐case patient's household (Table 2).
Table 1.
Descriptive characteristics of households and contacts in control arm, Bangladesh Interruption of Secondary Transmission of Influenza Study, Kishoreganj, Bangladesh (N = 363 households, 1491 contacts)
| Households (N = 363) | Contacts (N = 1491) | |
|---|---|---|
| n (%) | n (%) | |
| Index‐case patient household | 181 (49.9) | 722 (48.4) |
| Number of rooms in house | ||
| 1 | 183 (50.4) | 638 (42.8) |
| 2 | 109 (30.0) | 471 (31.6) |
| 3 | 47 (13.0) | 221 (14.8) |
| 4 or more | 24 (6.6) | 161 (10.8) |
| Mean (SD) number of people in household | 4.6 (2.0) | 5.5 (2.1) |
| Mean (SD) number of people per room | 3.1 (1.6) | 3.4 (1.7) |
| Building material of house | ||
| Wood/thatch | 17 (4.7) | 61 (4.1) |
| Tin | 68 (18.7) | 288 (19.3) |
| Brick/concrete | 278 (76.6) | 1142 (76.6) |
| Biomass fuel use | 345 (95.0) | 1441 (96.7) |
| Mean (SD) number of steps from sleeping space to cooking space | 7.9 (6.0) | 8.0 (5.9) |
| Cooking space separated from living spacea | 312 (86.0) | 1290 (86.5) |
| Smoking in house | ||
| Ever | 251 (69.1) | 1055 (70.8) |
| Never | 112 (30.9) | 436 (29.2) |
| Materials at handwashing station | ||
| Neither soap nor water | 45 (12.4) | 188 (12.6) |
| Water only | 252 (69.4) | 1016 (68.1) |
| Soap and water | 66 (18.2) | 287 (19.3) |
| Water source | ||
| Deep tube well | 238 (65.6) | 969 (65.0) |
| Shallow tube well | 114 (31.4) | 478 (32.1) |
| Other | 11 (3.0) | 44 (3.0) |
| Improved latrine use | 258 (71.1) | 1047 (70.2) |
| Private latrine | 117 (32.2) | 548 (36.8) |
| Share latrine with one other household | 100 (27.6) | 401 (26.9) |
| Share latrine with >1 other household | 146 (40.2) | 542 (36.4) |
| Education level of respondentb | ||
| Less than 1 year | 141 (39.1) | 582 (39.3) |
| 1–4 years | 56 (15.5) | 241 (16.3) |
| 5–8 years | 100 (27.7) | 398 (26.9) |
| More than 8 years | 64 (17.7) | 261 (17.5) |
| SES quintile | ||
| Poorest | 83 (22.9) | 298 (20.0) |
| Second poorest | 78 (21.5) | 297 (19.9) |
| Middle | 70 (19.3) | 295 (19.8) |
| Second wealthiest | 66 (18.2) | 309 (20.7) |
| Wealthiest | 66 (18.2) | 292 (19.6) |
| Age of individual | ||
| <2 years | NA | 49 (3.3) |
| 2–4 years | 110 (7.4) | |
| 5–14 years | 378 (25.4) | |
| 15–49 years | 746 (50.0) | |
| ≥50 years | 208 (14.0) | |
Cooking space separated from living space indicates that there is at least one room between cooking space and living space or cooking space is not located in the same structure as the living space.
Nine individuals from two households are missing education level of respondent.
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Table 2.
Associations between household‐level risk factors and secondary influenza‐like illness (ILI) in BISTIS, Kishoreganj, Bangladesh (N = 1491)
| Secondary ILI (n = 114) n (%) | No ILI (n = 1377) n (%) | RR (95% CI)b | ARR (95% CI)c | |
|---|---|---|---|---|
| Index‐case patient lives in same household | 46 (40.4) | 676 (49.1) | 0.72 (0.49, 1.06) | 0.89 (0.62, 1.31) |
| Mean (SD) number of people per room | 3.5 (1.6) | 3.4 (1.7) | 1.04 (0.92, 1.17) | 1.00 (0.89, 1.13) |
| Building material of house | ||||
| Concrete/brick | 93 (81.6) | 1049 (76.2) | REF | REF |
| Tin | 16 (14.0) | 272 (19.8) | 0.68 (0.41, 1.13) | 0.74 (0.46, 1.19) |
| Wood/thatch | 5 (4.4) | 56 (4.1) | 1.01 (0.47, 2.18) | 0.82 (0.38, 1.78) |
| Mean (SD) number of steps from sleeping space to cooking space | 7.0 (4.6) | 8.0 (6.0) | 0.97 (0.93, 1.00) | 0.98 (0.94, 1.02) |
| Cooking space separated from living spacea | 99 (86.8) | 1191 (86.5) | 1.03 (0.65, 1.63) | 1.05 (0.68, 1.62) |
| Smoking in house | ||||
| Never | 19 (16.7) | 417 (30.3) | REF | REF |
| Ever | 95 (83.3) | 960 (69.7) | 2.07 (1.29, 3.30) | 1.91 (1.23, 2.96) |
| Materials at handwashing station | ||||
| Neither soap nor water | 22 (19.3) | 166 (12.1) | REF | REF |
| Water only | 71 (62.3) | 945 (68.6) | 0.60 (0.35, 1.01) | 0.71 (0.39, 1.28) |
| Soap and water | 21 (18.4) | 266 (19.3) | 0.63 (0.33, 1.19) | 0.97 (0.50, 1.86) |
| Water source | ||||
| Deep tube well | 76 (66.7) | 893 (64.9) | REF | REF |
| Shallow tube well | 35 (30.7) | 443 (32.2) | 0.93 (0.63, 1.38) | 1.06 (0.72, 1.55) |
| Other | 3 (2.6) | 41 (3.0) | 0.87 (0.30, 2.54) | 0.85 (0.33, 2.19) |
| Improved latrine use | 77 (67.5) | 970 (70.4) | 0.88 (0.50, 1.30) | 1.17 (0.79, 1.73) |
| Private latrine | 19 (16.7) | 529 (38.4) | REF | REF |
| Share latrine with one other household | 33 (29.0) | 368 (26.7) | 2.37 (1.35, 4.17) | 2.07 (1.18, 3.64) |
| Share latrine with >1 other household | 62 (54.4) | 480 (34.9) | 3.30 (1.94, 5.61) | 3.08 (1.81, 5.23) |
| P for trend | 0.003 | <0.0001 | ||
| Education level of respondent | ||||
| Less than 1 year | 47 (41.6) | 535 (39.1) | REF | REF |
| 1–4 years | 25 (22.1) | 216 (15.8) | 1.28 (0.76, 2.14) | 1.28 (0.77, 2.12) |
| 5–8 years | 27 (23.9) | 371 (27.1) | 0.84 (0.52, 1.34) | 1.04 (0.66, 1.63) |
| More than 8 years | 14 (12.4) | 247 (18.1) | 0.66 (0.37, 1.17) | 0.89 (0.52, 1.50) |
| P for trend | 0.3 | 0.8 | ||
| Wealth status quintile | ||||
| Poorest | 33 (29.0) | 265 (19.2) | REF | REF |
| Second poorest | 19 (16.7) | 278 (20.2) | 0.58 (0.33, 1.01) | 0.62 (0.32, 1.20) |
| Middle | 24 (21.1) | 271 (19.7) | 0.73 (0.43, 1.26) | 0.99 (0.59, 1.68) |
| Second wealthiest | 26 (21.9) | 284 (20.6) | 0.73 (0.43, 1.25) | 1.05 (0.62, 1.79) |
| Wealthiest | 13 (11.4) | 279 (20.3) | 0.40 (0.21, 0.79) | 0.68 (0.38, 1.22) |
| P for trend | 0.008 | 0.5 | ||
Cooking space separated from living space indicates that there is at least one room between cooking space and living space or cooking space is not located in the same structure as the living space.
Accounted for clustering on household level.
Adjusted for age category (<5, ≥5) of index‐case patient, ever smoking in the home, sharing a latrine with one other household or more than one other household, and accounted for clustering on household level.
This article is being made freely available through PubMed Central as part of the COVID-19 public health emergency response. It can be used for unrestricted research re-use and analysis in any form or by any means with acknowledgement of the original source, for the duration of the public health emergency.
In our final negative binomial regression models, we evaluated the independent associations between ever smoking in the home or sharing a latrine with one other household or more than one other household, and secondary ILI, adjusting for age category of the index‐case patient (<5, ≥5 years). Models examining smoking in the home were also adjusted for shared latrine use, and models examining shared latrine use were also adjusted for smoking in the home. All other models adjusted for both smoking in the home and shared latrine use. Sex and age of secondary contacts were not included as model covariates, as sex was not associated with risk of secondary ILI in bivariate analysis, and addition of age of the secondary contact did not substantially change model estimates. Addition of further covariates resulted in unstable models.
In our final models, the risk of developing secondary ILI was 91% (95% CI 1.23–2.96) greater in those who lived in a household in which smoking ever occurred, compared with those who lived in a household with no smoking. Additional adjustment for education, wealth quintile and each individual asset that weighed on the wealth measure (ownership of a chair, table, mobile phone, watch or clock, sewing machine and electricity in the home) did not substantially change the estimates of the relative risk for ILI among those who lived in a household where smoking occurred compared with those who did not (RRAdj between 1.85 and 1.94). Those who lived in a household with water at a handwashing station had a 29% lower risk of developing secondary ILI compared with those without water at a handwashing station, but this association was not statistically significant (95% CI 0.39–1.28). After adjustment, having soap and water at a handwashing station was not associated with risk of secondary ILI.
Compared with those living in a household with a private latrine, those who lived in households sharing their latrine with one other household were at a 2.07‐fold increased risk of developing secondary ILI (95% CI: 1.18, 3.64) and those who shared their latrine with more than one other household had a 3.08‐fold increased risk of developing secondary ILI (95% CI: 1.81, 5.23). Additional adjustment for education, wealth quintile and each individual asset that weighed on the wealth measure did not substantially change the estimates of the relative risk for ILI among those sharing a latrine with one other household (RRAdj between 1.98 and 2.10) or among those sharing a latrine with more than one other household (RRAdj between 3.00 and 3.12).
Living in the same household as an index‐case patient, crowding (number of people per room), building material of home, water source and improved latrine use were not associated with risk of secondary ILI. In stratified analysis, associations between household‐level risk factors and risk of secondary ILI did not substantially differ by age of index‐case patient. Sex of the secondary contact and relationship of the secondary contact to the index‐case patient were not associated with risk of developing secondary ILI in this analysis or in prior BISTIS analyses (results not shown) 30. Multiple interactions with the index‐case patient were not associated with shared latrine use or smoking in the home (results not shown).
Discussion
In this study of household‐level risk factors for ILI, we found that smoking in the home and sharing a latrine with other households were associated with increased risk of secondary ILI among household contacts. These results suggest that exposure to environmental tobacco smoke increases the risk of secondary ILI; there are several potential mechanisms for the increased risk of ILI due to shared latrine use. Both factors are potentially modifiable.
Our results support exposure to indoor air pollution from environmental tobacco smoke as a potential risk factor for ILI. Exposure to indoor air pollution is a well‐established risk factor for all‐cause acute respiratory infections, due to its detrimental effects on respiratory tissue and immune functioning in the respiratory tract 31, 32, 33. Exposure to environmental tobacco smoke is also a well‐established risk factor for numerous other conditions, including low birthweight, various cancers and chronic respiratory and cardiovascular diseases 34. The prevalence of smoking in the home was high in this study, highlighting the need for tobacco control measures in Bangladesh. Greater use of effective tobacco control measures, such as taxation, could help to reduce tobacco smoking prevalence in Bangladesh 35. The Global Adult Tobacco Survey estimated that 45% of adult men in Bangladesh smoke tobacco products 36. In contrast, only 1.5% of adult women in Bangladesh smoke. Our study showed a lower proportion of men who smoke (29%) compared with the Global Adult Tobacco Survey. In our study, the household head reported tobacco smoking for all members of the household; it is possible that respondents may underreport smoking habits of other household members. Although biomass fuels are considered to be the major source of indoor air pollution in low‐ and middle‐income countries 19, 32, 37, we were unable to assess the effect of biomass fuel use on secondary ILI, as nearly every participant (96.7%) reported using biomass fuels for cooking.
Sharing a latrine with at least one other household was the strongest exposure associated with secondary ILI observed in this study. Although shared latrines have not previously been shown to be associated with respiratory infections, there is some evidence of an association between shared latrines and diarrhoeal disease 38, 39. Shared latrines may not be cleaned as frequently as private latrines 38, so it is possible that pathogens remain present longer on surfaces in shared latrines compared with private latrines. Contact transmission, by either direct contact with infected fluids or indirect contact via fomites, may be an important route of transmission for influenza and other respiratory pathogens 40, 41 as well as diarrhoeal pathogens 38. Contaminated fomites in shared latrines, such as doors and traditional pots used for anal washing after defecation, may provide a route of transmission for pathogens in Bangladesh. As ILI may be caused by many different pathogens, it is possible that shared latrines may expose users to a number of different pathogens that may cause ILI symptoms. Specifically, influenza viruses 42, 43 and coronaviruses 44 have been recovered from faeces of patients, suggesting that some respiratory viruses may be transmitted through faecal contact. Interactions with people with influenza have been shown to be associated with risk of secondary influenza 45, 46, 47, 48, 49, and ILI 26; it is plausible that those who use shared sanitation may have increased interactivity due to a commonly used resource (latrine). We did not observe an association between multiple daily interactions with the index‐case patient and shared latrine use. However, we were unable to thoroughly investigate this possibility due to limited data. It is also possible that the association between sharing a latrine and ILI may be spurious or that latrine sharing represents a proxy for an unknown factor that is associated with ILI, but the effect estimates did not change substantially when adjusted for measures of wealth, age or smoking making this a less likely explanation.
Nearly 8% of household contacts reported ILI in this study. This proportion is similar to previous investigations of the burden of ILI in the general population of Bangladesh 5. Although age of the index‐case patient did not modify the effects of household‐level risk factors on ILI, in this analysis and our prior analysis, ILI incidence was higher in susceptible contacts who were younger than 5 years compared with those who were 5 years or older 26. Residing in the index‐case patient's household was not associated with ILI risk, indicating that all members of a compound in a densely populated area are at risk of contracting infectious diseases from their compound members or the community at large.
Important limitations of this study include lack of detail regarding intra‐ vs. extra‐household transmission pathways. We do not know whether pathogens were transmitted between members of the same household compound, whether they were acquired outside of the compound or whether the index‐case patient we identified is in fact the primary ILI case in each compound. It is possible that control households had contact with intervention households and subsequently modified handwashing behaviour. However, our main study results do not suggest an association between handwashing and secondary ILI, so contact with the intervention arm is unlikely to have affected our results. As few participants had influenza, we did not test for other pathogens, and our definition of ILI for those under 5 years was broad, our results may not be relevant to influenza transmission, but rather, transmission of respiratory pathogens more broadly. Air pollution is a well‐established household‐level risk factor for respiratory illness 31, 32, 33, but reliable data on concentrations of household air pollutants are not available from this study. However, we did observe associations between indoor smoking, one proxy indicator of air pollution and secondary ILI incidence. As this study recruited participants from selected healthcare facilities, our sample may not be representative of people who sought care elsewhere 3, 5. In addition, our sample may not be generalisable to urban Bangladesh, where there may be more crowding and more accessible health care.
Conclusions
Smoking in the home and use of shared latrines are associated with an increased risk of secondary influenza‐like illness in households in this study. Our data highlight the possible benefit of efforts to reduce exposure to indoor air pollution from environmental tobacco smoke, including effective approaches to smoking cessation and clean air initiatives. Interventions focused on improving access to private latrines may also be helpful in low‐income countries.
Acknowledgements
First, we would like to thank the participants of BISTIS for their time and patience. We would like to thank our field staff for all of their hard work. This research study was funded by US Centers for Disease Control and Prevention. icddr,b acknowledges with gratitude the commitment of CDC to its research efforts. icddr,b also gratefully acknowledges the following donors who provide unrestricted support: Government of the People's Republic of Bangladesh; Global Affairs Canada; Swedish International Development Cooperation Agency and the Department for International Development. The findings and conclusions in his report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
References
- 1. Brooks WA, Terebuh P, Bridges C et al Influenza A and B infection in children in urban slum, Bangladesh. Emerg Infect Dis 2007: 13: 1507–1508. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Brooks WA, Goswami D, Rahman M et al Influenza is a major contributor to childhood Pneumonia in a tropical developing country. Pediatr Infect Dis J. 2010: 29: 216–221. [DOI] [PubMed] [Google Scholar]
- 3. Azziz‐Baumgartner E, Alamgir AS, Rahman M et al Incidence of influenza‐like illness and severe acute respiratory infection during three influenza seasons in Bangladesh, 2008‐2010. Bull World Health Organ 2012: 90: 12–19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Morgan OW, Parks S, Shim T et al Household transmission of pandemic (H1N1) 2009, San Antonio, Texas, USA, April‐May 2009. Emerg Infect Dis 2010: 16: 631–637. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Homaira N, Luby SP, Alamgir AS et al Influenza‐associated mortality in 2009 in four sentinel sites in Bangladesh. Bull World Health Organ 2012: 90: 272–278. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Bhuiyan MU, Luby SP, Alamgir NI et al Economic burden of influenza‐associated hospitalizations and outpatient visits in Bangladesh during 2010. Influenza Other Respir Viruses 2014: 8: 406–413. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. International Centre for Diarrhoeal Disease Research Bangladesh . The economic burden of influenza‐like illness in Mirpur, Dhaka, during the 2009 pandemic: a household cost of illness study. Health Sci Bull 2010: 8: 12–18. [Google Scholar]
- 8. Bridges CB, Kuehnert MJ, Hall CB. Transmission of influenza: implications for control in health care settings. Clin Infect Dis 2003: 37: 1094–1101. [DOI] [PubMed] [Google Scholar]
- 9. Luby SP, Brooks WA, Zaman K, Hossain S, Ahmed T. Infectious diseases and vaccine sciences: strategic directions. J Health Popul Nutr 2008: 26: 295–310. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Cauchemez S, Bhattarai A, Marchbanks TL et al Role of social networks in shaping disease transmission during a community outbreak of 2009 H1N1 pandemic influenza. PNAS 2011: 108: 2825–2830. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Cowling BJ, Chan KH, Fang VJ et al Facemasks and hand hygiene to prevent influenza transmission in households: a cluster randomized trial [Summary for patients in Ann Intern Med. 2009 Oct 6;151(7):I‐18; PMID: 19805764]. Ann Intern Med 2009: 151: 437–446. [DOI] [PubMed] [Google Scholar]
- 12. Al‐Khatib I, Ju'ba A, Kamal N, Hamed N, Hmeidan N, Massad S. Impact of housing conditions on the health of the people at al‐Ama'ri refugee camp in the West Bank of Palestine. Int J Environ Health Res 2003: 13: 315–326. [DOI] [PubMed] [Google Scholar]
- 13. Luby SP, Agboatwalla M, Feikin DR et al Effect of handwashing on child health: a randomised controlled trial. Lancet 2005: 366: 225–233. [DOI] [PubMed] [Google Scholar]
- 14. Tang JW, Li Y, Eames I, Chan PKS, Ridgway GL. Factors involved in the aerosol transmission of infection and control of ventilation in healthcare premises. J Hosp Infect 2006: 64: 100–114. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Tumwesigire SG, Barton T. Environmental risk factors for acute respiratory infections among children of military personnel in Uganda. East Afr Med J 1995: 72: 290–294. [PubMed] [Google Scholar]
- 16. Jefferson T, Foxlee R, Del Mar C et al Physical interventions to interrupt or reduce the spread of respiratory viruses: systematic review. BMJ 2009: 336: 77–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Talaat M, Afifi S, Dueger E et al Effects of hand hygiene campaigns on incidence of laboratory‐confirmed influenza and absenteeism in schoolchildren, Cairo, Egypt. Emerg Infect Dis 2011: 17: 619–625. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Ezzati M, Saleh H, Kammen DM. The contributions of emissions and spatial microenvironments to exposure to indoor air pollution from biomass combustion in Kenya. Environ Health Perspect 2000: 108: 833–839. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Emmelin A, Wall S. Indoor air pollution: a poverty‐related cause of mortality among the children of the world. Chest 2007: 132: 1615–1623. [DOI] [PubMed] [Google Scholar]
- 20. Gurley ES, Homaira N, Salje H et al Indoor exposure to particulate matter and the incidence of acute lower respiratory infections among children: a birth cohort study in urban Bangladesh. Indoor Air 2013: 23: 379–386. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Gurley ES, Salje H, Homaira N. Indoor exposure to particulate matter and age at first acute lower respiratory infection in a low‐income urban community in Bangladesh. Am J Epidemiol 2014: 179: 967–973. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Holgate ST, Samet JM, Koren HS, Maynard RL (eds). Air Pollution and Health. Academic Press: San Diego, California, 1999. [Google Scholar]
- 23. McGrath JJ, Barnes CD (eds). Air Pollution–Physiological Effects. Academic Press: New York, 1982. [Google Scholar]
- 24. Smith KR, Mehta S. The burden of disease from indoor air pollution in developing countries: comparison of estimates. Int J Hyg Environ Health 2003: 206: 279–289. [DOI] [PubMed] [Google Scholar]
- 25. Crabtree‐Ide CR, Rudra CB, Silk BJ et al (eds). Household factors associated with indoor air pollution in a low‐income urban area in Bangladesh American Society of Tropical Medicine and Hygiene Annual Meeting; 2011 December 5, 2011; Philadelphia, PA.
- 26. Ram PK, DiVita MA, Khatun‐e‐Jannat K et al Impact of intensive handwashing promotion on secondary household influenza‐like illness in rural Bangladesh: findings from a randomized controlled trial. PLoS One 2015: 10: 1–18. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. World Health Organization . Manual for the Laboratory Diagnosis and Virological Surveillance of Influenza. World Health Organization: Geneva, Switzerland, 2011. [Google Scholar]
- 28. Ram PK. Practical Guidance for Measuring Handwashing Behavior, 2010.
- 29. Filmer D, Pritchett LH. Estimating wealth effects without expenditure data–or tears: an application to educational enrollments in states of India. Demography 2001: 38: 115–132. [DOI] [PubMed] [Google Scholar]
- 30. Ram PK, Islam M, Jannat K et al Individual level risk factors for secondary transmission of influenza‐like illness: secondary data analysis from the Bangladesh Interruption of Secondary Transmission of Influenza Study (BISTIS) American Society of Tropical Medicine and Hygiene Annual Meeting; Atlanta, GA, 2012.
- 31. Ram PK, Dutt D, Sil BJ et al Household air quality risk factors associated with childhood pneumonia in urban Dhaka, Bangladesh. Am J Trop Med Hyg 2014: 90: 968–975. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Smith KR, Samet JM, Romieu I, Bruce N. Indoor air pollution in developing countries and acute lower respiratory infections in children. Thorax 2000: 55: 518–532. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Grigg J. Effect of biomass smoke on pulmonary host defence mechanisms. Paediatr Respir Rev 2007: 8: 287–291. [DOI] [PubMed] [Google Scholar]
- 34. World Health Organization Tobacco Free Initiative . International Consultation on Environmental Tobacco Smoke (ETS) and Child Health. World Health Organization Tobacco Free Initiative: Geneva, Switzerland, 1999. [Google Scholar]
- 35. Nargis N, Ruthbah UH, Ghulam Hussain AKM, Fong GT, Huq I, Ashiquzzaman SM. The price sensitivity of cigarette consumption in Bangladesh: evidence from the International Tobacco Control (ITC) Bangladesh Wave 1 (2009) and Wave 2 (2010) surveys. Tobacco Control 2013: Suppl 1:i39–47. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Giovino G, Mirza SA, Samet JM et al Tobacco use in 3 billion individuals from 16 countries: an analysis of nationally representative cross‐sectional household surveys. Lancet 2012: 380: 668–679. [DOI] [PubMed] [Google Scholar]
- 37. Smith KR. Indoor air pollution in developing countries: recommendations for research. Indoor Air 2002: 12: 198–207. [DOI] [PubMed] [Google Scholar]
- 38. Fuller JA, Clasen T, Heijnen M, Eisenberg JNS. Shared sanitation and the prevalence of diarrhea in young children: evidence from 51 countries, 2001‐2011. Am J Trop Med Hyg 2014: 91: 173–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Heijnen M, Cumming O, Peletz R et al Shared sanitation versus individual household latrines: a systematic review of health outcomes. PLoS One 2014: 9: 1–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40. Wong VWY, Cowling BJ, Aiello AE. Hand hygiene and risk of influenza virus infections in the community: a systematic review and meta‐analysis. Epidemiol Infect 2014: 142: 922–932. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41. Walther BA, Ewald PW. Pathogen survival in the external environment and the evolution of virulence. Biol Rev Camb Philos Soc 2004: 79: 849–869. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42. Dilantika C, Sedyaningsih ER, Kasper MR et al Influenza virus infection among pediatric patients reporting diarrhea and influenza‐like illness. BMC Infect Dis 2010: 10: 3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43. Buchy P, Mardy S, Vong S et al Influenza A/H5N1 virus infection in humans in Cambodia. J Clin Virol 2007: 39: 164–168. [DOI] [PubMed] [Google Scholar]
- 44. Jevsnik M, Steyer A, Zrim T et al Detection of human coronaviruses in simultaneously collected stool samples and nasopharyngeal swabs from hospitalized children with acute gastroenteritis. Virol J 2013: 10: 46. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45. Eames KT, Tilston NL, Brooks‐Pollock E, Edmunds WJ. Measured dynamic social contact patterns explain the spread of H1N1v influenza. PLoS Comput Biol 2012: 8: e1002425. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46. Melegaro A, Jit M, Gay N, Zagheni E, Edmunds WJ. What types of contacts are important for the spread of infections?: using contact survey data to explore European mixing patterns. Epidemics 2011: 3: 143–151. [DOI] [PubMed] [Google Scholar]
- 47. Mossong J, Hens N, Jit M et al Social contacts and mixing patterns relevant to the spread of infectious diseases. PLoS Med 2008: 5: e74. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48. Read JM, Lessler J, Riley S et al Social mixing patterns in rural and urban areas of southern China. Proc Biol Sci 2014: 281: 20140268. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49. Wallinga J, Teunis P, Kretzschmar M. Using data on social contacts to estimate age‐specific transmission parameters for respiratory‐spread infectious agents. Am J Epidemiol 2006: 164: 936–944. [DOI] [PubMed] [Google Scholar]