VIRUSES
Respiratory syncytial virus seasonality in tropical Australia Stuart Paynter,1 Robert S. Ware,1,2 Peter D. Sly,2 Philip Weinstein,3,4 Gail Williams1
R
espiratory syncytial virus (RSV) is the most common cause of acute lower respiratory infection in infants. It is estimated that, globally, RSV is responsible for one out of every 15 deaths in post-neonatal infants (children aged 1 to 12 months).1 In Australia it is estimated that 16 of every 1,000 infants are hospitalised as a result of RSV infection.2 A clear understanding of local RSV epidemiology is essential for optimal control efforts. This includes an understanding of the environmental drivers of RSV transmission. Several studies have examined RSV incidence in low- to middle-income settings with tropical climates. In general, RSV incidence appears to be highest during the rainy season, however this is not always the case, suggesting different environmental drivers may predominate in different settings.3-5 The most likely drivers in these low- to middle-income settings are seasonal changes in rainfall and humidity (in turn, affecting host behaviour and viral survival) and seasonal malnutrition.6-8 The available evidence suggests that RSV incidence in tropical Australia is linked to the rainy season,9, 10 however formal time series analysis of RSV seasonality has not been performed to date. In this study we examine the seasonal variation in RSV hospital admissions over 12.8 years in two sites in North Queensland (Cairns and Townsville) and assess potential environmental drivers of this seasonality.
Abstract Objective: Respiratory syncytial virus (RSV) is most common during the rainy season in a number of low- to middle-income tropical settings, a pattern driven by seasonal changes in climate and nutrition. We investigated the seasonality of RSV in the high-income tropical setting of North Queensland, Australia. Methods: We used RSV hospital admissions data from Cairns and Townsville to assess the seasonality of RSV. We examined the seasonal scale associations between selected meteorological exposures and RSV admissions using cross-correlation of weekly data. Results: In both Cairns and Townsville, RSV admissions were highest in the latter half of the rainy season. In Cairns, RSV admissions were most strongly correlated with rainfall four weeks previously. In Townsville, RSV admissions were most strongly correlated with rainfall six weeks previously. Conclusions: The seasonality of RSV in the tropical setting of North Queensland appears to be driven by seasonal variations in rainfall. Further research is needed to assess the impact of climate on RSV incidence in the tropics. Key words: Respiratory syncytial virus, seasonality, climate, tropical health
Methods RSV admissions data for Cairns and Townsville from July 1999 to March 2012 were obtained from Queensland Health. This data includes all children under five years who were resident in Cairns or Townsville, and admitted to either Cairns or Townsville hospital with confirmed RSV infection, during the study period. Meteorological data are from the Australian Bureau of Meteorology. Ethical approval for the use of the admissions data was obtained from the University of Queensland School of Population Health Research Ethics Committee (approval SP270212).
We performed an initial descriptive analysis of the data by plotting the number of RSV admissions at each site according to the calendar week of admission, and comparing this with the means of the following meteorological exposures for each calendar week: maximum temperature, daily rainfall, relative humidity (measured at 9 am), dew point (measured at 9 am), daily total solar radiation (in MJm-2), and daily sunshine hours (in tropical latitudes sunshine hours give a proxy measure of cloud cover). Statistical testing of the seasonal scale associations between meteorological exposures and RSV admissions was performed using
1. School of Public Health, University of Queensland 2. Queensland Children’s Medical Research Institute, University of Queensland 3. Faculty of Science, University of Adelaide, South Australia 4. School of Pharmacy and Health Sciences, University of South Australia Correspondence to: Dr Stuart Paynter, School of Public Health, Level 2, Public Health Building, University of Queensland, Herston Road, Herston, Queensland 4006; e-mail: [email protected] Submitted: June 2014; Revision requested: October 2014; Accepted: October 2014 The authors have stated they have no conflict of interest. Aust NZ J Public Health. 2015; 39:8-10; doi: 10.1111/1753-6405.12347
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Australian and New Zealand Journal of Public Health © 2015 Public Health Association of Australia
2015 vol. 39 no. 1
Viruses
RSV in tropical Australia
cross-correlation of weekly data over the 12.5 year study period (six weeks at the beginning and end of the time series were lost due to seasonal smoothing). Data were smoothed using a three month (13 week) moving average prior to the cross-correlation analysis, in order to focus on the seasonal scale association. All data analysis used Stata (version 12).
The seasonal peak in RSV incidence in Cairns and Townsville occurs in the latter part of the rainy season, following four to six weeks after peak rainfall. This four to six week lag is consistent with the results of mathematical modelling of RSV transmission, which
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Figure 2: Seasonality of RSV and meteorological exposures in Townsville. Total numbers of RSV admissions over the study period, and mean values of meteorological parameters over the study period, according to calendar week.
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Table 1: Cross-correlation results showing the lag between RSV admissions and meteorological exposures at maximum correlation. A negative lag denotes the exposure occurring before the outcome (for example RSV admissions in Cairns are most strongly correlated with rainfall four weeks earlier). Lag at maximum correlation (weeks)
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Cross-correlations were performed for rainfall, relative humidity and sunshine hours. Results of the cross-correlations are shown in Table 1. In Cairns, RSV admissions were most strongly correlated with rainfall four weeks earlier, while in Townsville, RSV admissions were most strongly correlated with rainfall six weeks earlier.
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Rainfall (mm day-1) / Sunshine (hrs day-1) / Temperature (°C) / Solar radiation (MJ m-2 day-1)
The seasonality of RSV admissions was regular over the study period. In Cairns, peak RSV incidence occurred mostly during March, while in Townsville, peak RSV incidence was mostly in March/April. Figures 1 and 2 demonstrate the seasonality of RSV admissions in Cairns and Townsville, showing the total numbers of RSV admissions over the study period, according to calendar week of admission. Also shown are the mean values of meteorological parameters over the study period for each site. Rainfall and relative humidity are both maximal in the weeks before the peak in RSV incidence. The other meteorological variables are less clearly related to RSV incidence in these sites.
Exposure
predicts that environmental drivers of RSV seasonality act about 1-2 months before the peak in RSV incidence.11, 12 If rainfall is driving RSV transmission in these settings, the shorter lag in Cairns could be due to the more intense seasonal rainfall in Cairns: mathematical modelling predicts a shorter lag following a
Figure 1: Seasonality of RSV and meteorological exposures in Cairns. Total numbers of RSV admissions over the study period, and mean values of meteorological parameters over the study period, according to calendar week.
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Article
stronger forcing of transmission.12 The results of our study show that the seasonality of RSV in North Queensland is similar to that of several nearby tropical settings, such as Indonesia, Malaysia, the Philippines, and Thailand.3,13,14 In contrast, the seasonality of RSV in temperate Australia is similar to that in temperate zones in the Northern Hemisphere, with peak RSV incidence in the winter.15 This tropical/temperate difference in RSV seasonality in Australia suggests that meteorological factors may be more important in driving RSV seasonality in Australia than socioeconomic factors such as nutrition. It also suggests that school holidays do not play a major role in determining RSV seasonality. A similar finding has been noted in the United States, where the RSV season commences 2-3 months earlier in subtropical Florida than in the rest of the country.16 The cold and dry conditions of temperate winters favour RSV survival in the environment (and may encourage people to crowd together indoors).6, 17 It is less clear how high rainfall and humidity could drive RSV transmission in tropical climates. The effects of high humidity on RSV are not clear. Relative humidity above 80% (at room temperature) may delay the drying of large respiratory droplets,18-20 which could favour RSV survival and transmission since RSV is predominantly transmitted by large droplets.21, 22 In tropical settings, however, high humidity is generally accompanied by high temperature, which appears to reduce RSV survival.17 The net effect of these exposures is unknown. In addition, indoor temperature and humidity may be quite different to outdoor conditions. Increased rainfall (and cloud cover) may lead to people spending more time indoors, however the difference appears to be small compared to the total amount of time spent indoors. In a US study looking at individuals of all ages, people spent an average of 87.0% of their time indoors on dry days, and 89.5% of their time indoors on rainy days (percentages of a total 24-hour period).23 It is possible that increased time indoors away from the home on rainy days may increase the chance of parents and older siblings acquiring RSV infection and passing it on to infants in the home. A study from the tropical setting of Bangladesh found an increased risk of respiratory infection following rainy days only in households with three or more people per room, suggesting a link between rainfall and crowding.24
10
Our results indicate that climate is a strong predictor of RSV transmissibility, independent of known socioeconomic determinants such as crowding and malnutrition.25-27 If high levels of rainfall and humidity do indeed increase the transmissibility of RSV this could have implications for many living in the tropics, as recent projections from the Intergovernmental Panel on Climate Change indicate monsoon systems will intensify, last longer and cover a larger geographical area than currently.28 As well as leading to more obvious phenomena such as seasonality, environmental drivers of transmission (either meteorological or socioeconomic) increase the overall force of infection acting on the population, which in turn will reduce the average age of first infection.29 The younger a child is at their first RSV infection, the more severe the disease.30 Further efforts to determine the environmental mechanisms acting on RSV transmission (and how these may change in the future) are necessary to optimise RSV control.
References 1. Lozano R, Naghavi M, Foreman K, Lim S, Shibuya K, Aboyans V, et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380(9859):2095-128. 2. Ranmuthugala G, Brown L, Lidbury BA. Respiratory syncytial virus-the unrecognised cause of health and economic burden among young children in Australia. Commun Dis Intell Q Rep. 2011;35(2):177. 3. Weber MW, Mulholland EK, Greenwood BM. Respiratory syncytial virus infection in tropical and developing countries. Trop Med Int Health. 1998;3(4):268-80. 4. van der Sande MA, Goetghebuer T, Sanneh M, Whittle HC, Weber MW. Seasonal variation in respiratory syncytial virus epidemics in the Gambia, West Africa. Pediatr Infect Dis J. 2004;23(1):73-4. 5. Robertson SE, Roca A, Alonso P, Simoes EA, Kartasasmita CB, Olaleye DO, et al. Respiratory syncytial virus infection: Denominator-based studies in Indonesia, Mozambique, Nigeria and South Africa. Bull World Health Organ. 2004;82(12):914-22. 6. Tang JW. The effect of environmental parameters on the survival of airborne infectious agents. J R Soc Interface. 2009;6 Suppl 6:S737-S46. 7. Tamerius J, Nelson MI, Zhou SZ, Viboud C, Miller MA, Alonso WJ. Global influenza seasonality: Reconciling patterns across temperate and tropical regions. Environ Health Perspect. 2011;119(4):439. 8. Paynter S, Ware R, Lucero M, Tallo V, Nohynek H, Simões E, et al. Poor growth and pneumonia seasonality in infants in the Philippines: Cohort and time series studies. PLOS One. 2013;8(6):e67528. 9. Reeve CA, Whitehall JS, Buettner PG, Norton R, Reeve DM, Francis F. Cost-effectiveness of respiratory syncytial virus prophylaxis with palivizumab. J Paediatr Child Health. 2006;42(5):253-8. 10. O’Grady K-AF, Torzillo PJ, Chang AB. Hospitalisation of Indigenous children in the Northern Territory for lower respiratory illness in the first year of life. Med J Aust. 2010;192(10):586. 11. Weber A, Weber M, Milligan P. Modeling epidemics caused by respiratory syncytial virus (RSV). Math Biosci. 2001;172(2):95-113.
12. Paynter S, Yakob L, Simões E, Lucero M, Tallo V, Nohynek H, et al. Using mathematical transmission modelling to investigate drivers of respiratory syncytial virus seasonality in children in the Philippines. PLOS One. 2014;9(2):e90094. 13. Omer SB, Sutanto A, Sarwo H, Linehan M, Djelantik IGG, Mercer D, et al. Climatic, temporal, and geographic characteristics of respiratory syncytial virus disease in a tropical island population. Epidemiol Infect. 2008;136(10):1319-27. 14. Chan PWK, Chew FT, Tan TN, Chua KB, Hooi PS. Seasonal variation in respiratory syncytial virus chest infection in the tropics. Pediatr Pulmonol. 2002;34(1):47-51. 15. Lazzaro T, Hogg G, Barnett P. Respiratory syncytial virus infection and recurrent wheeze/asthma in children under five years: An epidemiological survey. J Paediatr Child Health. 2007;43(1‐2):29-33. 16. Yusuf S, Piedimonte G, Auais A, Demmler G, Krishnan S, Van Caeseele P, et al. The relationship of meteorological conditions to the epidemic activity of respiratory syncytial virus. Epidemiol Infect. 2007;135(7):1077-90. 17. Hambling M. Survival of the respiratory syncytial virus during storage under various conditions. Br J Exp Pathol. 1964;45(6):647. 18. Kingston D. Towards the isolation of respiratory syncytial virus from the environment. J Appl Microbiol. 1968;31(4):498-510. 19. Buckland F, Tyrrell D. Loss of infectivity on drying various viruses. Nature. 1962;195:1063-4. 20. Yang W, Elankumaran S, Marr LC. Relationship between humidity and influenza A viability in droplets and implications for influenza’s seasonality. PLOS One. 2012;7(10):e46789. 21. Hall CB, Douglas Jr RG. Modes of transmission of respiratory syncytial virus. J Pediatr. 1981;99(1):100-3. 22. Leclair JM, Freeman J, Sullivan BF, Crowley CM, Goldmann DA. Prevention of nosocomial respiratory syncytial virus infections through compliance with glove and gown isolation precautions. N Engl J Med. 1987;317(6):329-34. 23. Graham SE, McCurdy T. Developing meaningful cohorts for human exposure models. J Expo Sci Environ Epidemiol. 2004;14(1):23-43. 24. Murray E, Klein M, Brondi L, McGowan J, Van Mels C, Brooks W, et al. Rainfall, household crowding, and acute respiratory infections in the tropics. Epidemiol Infect. 2012;140:78-86. 25. Colosia AD, Masaquel A, Hall CB, Barrett AM, Mahadevia PJ, Yogev R. Residential crowding and severe respiratory syncytial virus disease among infants and young children: A systematic literature review. BMC Infect Dis. 2012;12(1):95. 26. Okiro EA, Ngama M, Bett A, Cane PA, Medley GF, James Nokes D. Factors associated with increased risk of progression to respiratory syncytial virus associated pneumonia in young Kenyan children. Trop Med Int Health. 2008;13(7):914-26. 27. Paynter S, Ware RS, Lucero MG, Tallo V, Nohynek H, Weinstein P, et al. Malnutrition: A Risk Factor for Severe Respiratory Syncytial Virus Infection and Hospitalization. Pediatr Infect Dis J. 2014;33(3):267-71. 28. Intergovernmental Panel on Climate Change. Climate Change 2013: The Physical Science Basis. Summary for Policymakers. Bern (CHE): IPCC WGI TSU; 2013. 29. Anderson R, May R. Infectious Disease of Humans: Dynamics and Control. Oxford (UK): Oxford University Press, 1991. 30. Ohuma E, Okiro E, Ochola R, Sande C, Cane P, Medley G, et al. The natural history of respiratory syncytial virus in a birth cohort: The influence of age and previous infection on reinfection and disease. Am J Epidemiol. 2012;176(9):794-802.
Australian and New Zealand Journal of Public Health © 2015 Public Health Association of Australia
2015 vol. 39 no. 1
Respiratory syncytial virus seasonality in tropical Australia Stuart Paynter,1 Robert S. Ware,1,2 Peter D. Sly,2 Philip Weinstein,3,4 Gail Williams1
R
espiratory syncytial virus (RSV) is the most common cause of acute lower respiratory infection in infants. It is estimated that, globally, RSV is responsible for one out of every 15 deaths in post-neonatal infants (children aged 1 to 12 months).1 In Australia it is estimated that 16 of every 1,000 infants are hospitalised as a result of RSV infection.2 A clear understanding of local RSV epidemiology is essential for optimal control efforts. This includes an understanding of the environmental drivers of RSV transmission. Several studies have examined RSV incidence in low- to middle-income settings with tropical climates. In general, RSV incidence appears to be highest during the rainy season, however this is not always the case, suggesting different environmental drivers may predominate in different settings.3-5 The most likely drivers in these low- to middle-income settings are seasonal changes in rainfall and humidity (in turn, affecting host behaviour and viral survival) and seasonal malnutrition.6-8 The available evidence suggests that RSV incidence in tropical Australia is linked to the rainy season,9, 10 however formal time series analysis of RSV seasonality has not been performed to date. In this study we examine the seasonal variation in RSV hospital admissions over 12.8 years in two sites in North Queensland (Cairns and Townsville) and assess potential environmental drivers of this seasonality.
Abstract Objective: Respiratory syncytial virus (RSV) is most common during the rainy season in a number of low- to middle-income tropical settings, a pattern driven by seasonal changes in climate and nutrition. We investigated the seasonality of RSV in the high-income tropical setting of North Queensland, Australia. Methods: We used RSV hospital admissions data from Cairns and Townsville to assess the seasonality of RSV. We examined the seasonal scale associations between selected meteorological exposures and RSV admissions using cross-correlation of weekly data. Results: In both Cairns and Townsville, RSV admissions were highest in the latter half of the rainy season. In Cairns, RSV admissions were most strongly correlated with rainfall four weeks previously. In Townsville, RSV admissions were most strongly correlated with rainfall six weeks previously. Conclusions: The seasonality of RSV in the tropical setting of North Queensland appears to be driven by seasonal variations in rainfall. Further research is needed to assess the impact of climate on RSV incidence in the tropics. Key words: Respiratory syncytial virus, seasonality, climate, tropical health
Methods RSV admissions data for Cairns and Townsville from July 1999 to March 2012 were obtained from Queensland Health. This data includes all children under five years who were resident in Cairns or Townsville, and admitted to either Cairns or Townsville hospital with confirmed RSV infection, during the study period. Meteorological data are from the Australian Bureau of Meteorology. Ethical approval for the use of the admissions data was obtained from the University of Queensland School of Population Health Research Ethics Committee (approval SP270212).
We performed an initial descriptive analysis of the data by plotting the number of RSV admissions at each site according to the calendar week of admission, and comparing this with the means of the following meteorological exposures for each calendar week: maximum temperature, daily rainfall, relative humidity (measured at 9 am), dew point (measured at 9 am), daily total solar radiation (in MJm-2), and daily sunshine hours (in tropical latitudes sunshine hours give a proxy measure of cloud cover). Statistical testing of the seasonal scale associations between meteorological exposures and RSV admissions was performed using
1. School of Public Health, University of Queensland 2. Queensland Children’s Medical Research Institute, University of Queensland 3. Faculty of Science, University of Adelaide, South Australia 4. School of Pharmacy and Health Sciences, University of South Australia Correspondence to: Dr Stuart Paynter, School of Public Health, Level 2, Public Health Building, University of Queensland, Herston Road, Herston, Queensland 4006; e-mail: [email protected] Submitted: June 2014; Revision requested: October 2014; Accepted: October 2014 The authors have stated they have no conflict of interest. Aust NZ J Public Health. 2015; 39:8-10; doi: 10.1111/1753-6405.12347
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Australian and New Zealand Journal of Public Health © 2015 Public Health Association of Australia
2015 vol. 39 no. 1
Viruses
RSV in tropical Australia
cross-correlation of weekly data over the 12.5 year study period (six weeks at the beginning and end of the time series were lost due to seasonal smoothing). Data were smoothed using a three month (13 week) moving average prior to the cross-correlation analysis, in order to focus on the seasonal scale association. All data analysis used Stata (version 12).
The seasonal peak in RSV incidence in Cairns and Townsville occurs in the latter part of the rainy season, following four to six weeks after peak rainfall. This four to six week lag is consistent with the results of mathematical modelling of RSV transmission, which
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Figure 2: Seasonality of RSV and meteorological exposures in Townsville. Total numbers of RSV admissions over the study period, and mean values of meteorological parameters over the study period, according to calendar week.
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Table 1: Cross-correlation results showing the lag between RSV admissions and meteorological exposures at maximum correlation. A negative lag denotes the exposure occurring before the outcome (for example RSV admissions in Cairns are most strongly correlated with rainfall four weeks earlier). Lag at maximum correlation (weeks)
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Cross-correlations were performed for rainfall, relative humidity and sunshine hours. Results of the cross-correlations are shown in Table 1. In Cairns, RSV admissions were most strongly correlated with rainfall four weeks earlier, while in Townsville, RSV admissions were most strongly correlated with rainfall six weeks earlier.
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The seasonality of RSV admissions was regular over the study period. In Cairns, peak RSV incidence occurred mostly during March, while in Townsville, peak RSV incidence was mostly in March/April. Figures 1 and 2 demonstrate the seasonality of RSV admissions in Cairns and Townsville, showing the total numbers of RSV admissions over the study period, according to calendar week of admission. Also shown are the mean values of meteorological parameters over the study period for each site. Rainfall and relative humidity are both maximal in the weeks before the peak in RSV incidence. The other meteorological variables are less clearly related to RSV incidence in these sites.
Exposure
predicts that environmental drivers of RSV seasonality act about 1-2 months before the peak in RSV incidence.11, 12 If rainfall is driving RSV transmission in these settings, the shorter lag in Cairns could be due to the more intense seasonal rainfall in Cairns: mathematical modelling predicts a shorter lag following a
Figure 1: Seasonality of RSV and meteorological exposures in Cairns. Total numbers of RSV admissions over the study period, and mean values of meteorological parameters over the study period, according to calendar week.
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stronger forcing of transmission.12 The results of our study show that the seasonality of RSV in North Queensland is similar to that of several nearby tropical settings, such as Indonesia, Malaysia, the Philippines, and Thailand.3,13,14 In contrast, the seasonality of RSV in temperate Australia is similar to that in temperate zones in the Northern Hemisphere, with peak RSV incidence in the winter.15 This tropical/temperate difference in RSV seasonality in Australia suggests that meteorological factors may be more important in driving RSV seasonality in Australia than socioeconomic factors such as nutrition. It also suggests that school holidays do not play a major role in determining RSV seasonality. A similar finding has been noted in the United States, where the RSV season commences 2-3 months earlier in subtropical Florida than in the rest of the country.16 The cold and dry conditions of temperate winters favour RSV survival in the environment (and may encourage people to crowd together indoors).6, 17 It is less clear how high rainfall and humidity could drive RSV transmission in tropical climates. The effects of high humidity on RSV are not clear. Relative humidity above 80% (at room temperature) may delay the drying of large respiratory droplets,18-20 which could favour RSV survival and transmission since RSV is predominantly transmitted by large droplets.21, 22 In tropical settings, however, high humidity is generally accompanied by high temperature, which appears to reduce RSV survival.17 The net effect of these exposures is unknown. In addition, indoor temperature and humidity may be quite different to outdoor conditions. Increased rainfall (and cloud cover) may lead to people spending more time indoors, however the difference appears to be small compared to the total amount of time spent indoors. In a US study looking at individuals of all ages, people spent an average of 87.0% of their time indoors on dry days, and 89.5% of their time indoors on rainy days (percentages of a total 24-hour period).23 It is possible that increased time indoors away from the home on rainy days may increase the chance of parents and older siblings acquiring RSV infection and passing it on to infants in the home. A study from the tropical setting of Bangladesh found an increased risk of respiratory infection following rainy days only in households with three or more people per room, suggesting a link between rainfall and crowding.24
10
Our results indicate that climate is a strong predictor of RSV transmissibility, independent of known socioeconomic determinants such as crowding and malnutrition.25-27 If high levels of rainfall and humidity do indeed increase the transmissibility of RSV this could have implications for many living in the tropics, as recent projections from the Intergovernmental Panel on Climate Change indicate monsoon systems will intensify, last longer and cover a larger geographical area than currently.28 As well as leading to more obvious phenomena such as seasonality, environmental drivers of transmission (either meteorological or socioeconomic) increase the overall force of infection acting on the population, which in turn will reduce the average age of first infection.29 The younger a child is at their first RSV infection, the more severe the disease.30 Further efforts to determine the environmental mechanisms acting on RSV transmission (and how these may change in the future) are necessary to optimise RSV control.
References 1. Lozano R, Naghavi M, Foreman K, Lim S, Shibuya K, Aboyans V, et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380(9859):2095-128. 2. Ranmuthugala G, Brown L, Lidbury BA. Respiratory syncytial virus-the unrecognised cause of health and economic burden among young children in Australia. Commun Dis Intell Q Rep. 2011;35(2):177. 3. Weber MW, Mulholland EK, Greenwood BM. Respiratory syncytial virus infection in tropical and developing countries. Trop Med Int Health. 1998;3(4):268-80. 4. van der Sande MA, Goetghebuer T, Sanneh M, Whittle HC, Weber MW. Seasonal variation in respiratory syncytial virus epidemics in the Gambia, West Africa. Pediatr Infect Dis J. 2004;23(1):73-4. 5. Robertson SE, Roca A, Alonso P, Simoes EA, Kartasasmita CB, Olaleye DO, et al. Respiratory syncytial virus infection: Denominator-based studies in Indonesia, Mozambique, Nigeria and South Africa. Bull World Health Organ. 2004;82(12):914-22. 6. Tang JW. The effect of environmental parameters on the survival of airborne infectious agents. J R Soc Interface. 2009;6 Suppl 6:S737-S46. 7. Tamerius J, Nelson MI, Zhou SZ, Viboud C, Miller MA, Alonso WJ. Global influenza seasonality: Reconciling patterns across temperate and tropical regions. Environ Health Perspect. 2011;119(4):439. 8. Paynter S, Ware R, Lucero M, Tallo V, Nohynek H, Simões E, et al. Poor growth and pneumonia seasonality in infants in the Philippines: Cohort and time series studies. PLOS One. 2013;8(6):e67528. 9. Reeve CA, Whitehall JS, Buettner PG, Norton R, Reeve DM, Francis F. Cost-effectiveness of respiratory syncytial virus prophylaxis with palivizumab. J Paediatr Child Health. 2006;42(5):253-8. 10. O’Grady K-AF, Torzillo PJ, Chang AB. Hospitalisation of Indigenous children in the Northern Territory for lower respiratory illness in the first year of life. Med J Aust. 2010;192(10):586. 11. Weber A, Weber M, Milligan P. Modeling epidemics caused by respiratory syncytial virus (RSV). Math Biosci. 2001;172(2):95-113.
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Australian and New Zealand Journal of Public Health © 2015 Public Health Association of Australia
2015 vol. 39 no. 1
