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    Age distribution of dengue cases for the period 2010–2014. Percentage of dengue cases in each age category over the entire study period.

  • View in gallery

    Time series and cross-correlation plots of climatic variables and dengue cases in Dhaka, from 2010 to 2014. (A) Time series of the monthly mean temperature, rainfall, and dengue cases. (B) Cross-correlation plot of monthly dengue cases and rainfall. (C) Cross-correlation plot of monthly dengue cases and temperature. The x axis gives the number of lags per month, and the y axis gives the value of the correlation coefficient between −1 and 1. Dotted lines indicate the 95% confidence level.

  • 1.

    Sharmin S, Viennet E, Glass K, Harley D, 2015. The emergence of dengue in Bangladesh: epidemiology, challenges and future disease risk. Trans R Soc Trop Med Hyg 109: 619627.

    • Search Google Scholar
    • Export Citation
  • 2.

    Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, Drake JM, Brownstein JS, Hoen AG, Sankoh O, Myers MF, George DB, Jaenisch T, Wint GR, Simmons CP, Scott TW, Farrar JJ, Hay SI, 2013. The global distribution and burden of dengue. Nature 496: 504507.

    • Search Google Scholar
    • Export Citation
  • 3.

    Pham HV, Doan HT, Phan TT, Minh NN, 2011. Ecological factors associated with dengue fever in a Central Highlands province, Vietnam. BMC Infect Dis 11: 172.

    • Search Google Scholar
    • Export Citation
  • 4.

    Johansson MA, Cummings DA, Glass GE, 2009. Multiyear climate variability and dengue—El Nino southern oscillation, weather, and dengue incidence in Puerto Rico, Mexico, and Thailand: a longitudinal data analysis. PLoS Med 6: e1000168.

    • Search Google Scholar
    • Export Citation
  • 5.

    Limkittikul K, Brett J, L'Azou M, 2014. Epidemiological trends of dengue disease in Thailand (2000–2011): a systematic literature review. PLoS Negl Trop Dis 8: e3241.

    • Search Google Scholar
    • Export Citation
  • 6.

    Bravo L, Roque VG, Brett J, Dizon R, L'Azou M, 2014. Epidemiology of dengue disease in the Philippines (2000–2011): a systematic literature review. PLoS Negl Trop Dis 8: e3027.

    • Search Google Scholar
    • Export Citation
  • 7.

    Quang Ha D, Quan Huan T, 1997. Dengue activity in Vietnam and its control programme 1997–1998. Dengue Bull 21: 3543.

  • 8.

    Karim MN, Munshi SU, Anwar N, Alam MS, 2012. Climatic factors influencing dengue cases in Dhaka city: a model for dengue prediction. Indian J Med Res 136: 3239.

    • Search Google Scholar
    • Export Citation
  • 9.

    Sharmin S, Glass K, Viennet E, Harley D, 2015. Interaction of mean temperature and daily fluctuation influences dengue incidence in Dhaka, Bangladesh. PLoS Negl Trop Dis 9: e0003901.

    • Search Google Scholar
    • Export Citation
  • 10.

    Sang CT, Hoon LS, Cuzzubbo A, Devine P, 1998. Clinical evaluation of a rapid immunochromatographic test for the diagnosis of dengue virus infection. Clin Diagn Lab Immunol 5: 407409.

    • Search Google Scholar
    • Export Citation
  • 11.

    Cuong HQ, Hien NT, Duong TN, Phong TV, Cam NN, Farrar J, Nam VS, Thai KT, Horby P, 2011. Quantifying the emergence of dengue in Hanoi, Vietnam: 1998–2009. PLoS Negl Trop Dis 5: e1322.

    • Search Google Scholar
    • Export Citation
  • 12.

    Xuan Le TT, Van Hau P, Thu Do T, Toan Do TT, 2014. Estimates of meteorological variability in association with dengue cases in a coastal city in northern Vietnam: an ecological study. Glob Health Action 7: 23119.

    • Search Google Scholar
    • Export Citation
  • 13.

    Velasco JM, Alera MT, Ypil-Cardenas CA, Dimaano EM, Jarman RG, Chinnawirotpisan P, Thaisomboonsuk B, Yoon IK, Cummings DA, Mammen MP Jr, 2014. Demographic, clinical and laboratory findings among adult and pediatric patients hospitalized with dengue in the Philippines. Southeast Asian J Trop Med Public Health 45: 337345.

    • Search Google Scholar
    • Export Citation
  • 14.

    Campbell KM, Lin CD, Iamsirithaworn S, Scott TW, 2013. The complex relationship between weather and dengue virus transmission in Thailand. Am J Trop Med Hyg 89: 10661080.

    • Search Google Scholar
    • Export Citation
  • 15.

    Faruque LI, Zaman RU, Alamgir AS, Gurley ES, Haque R, Rahman M, Luby SP, 2012. Hospital-based prevalence of malaria and dengue in febrile patients in Bangladesh. Am J Trop Med Hyg 86: 5864.

    • Search Google Scholar
    • Export Citation
  • 16.

    Bangladesh Bureau of Statistics, Ministry of Planning, 2010. Report of the Household Income and Expenditure Survey 2010. Dhaka, Bangladesh: Bangladesh Bureau of Statistics, 27.

    • Search Google Scholar
    • Export Citation
  • 17.

    Bhatia R, Dash AP, Sunyoto T, 2013. Changing epidemiology of dengue in south-east Asia. WHO South East Asia J Public Health 2: 2327.

  • 18.

    Nisalak A, Endy TP, Nimmannitya S, Kalayanarooj S, Thisayakorn U, Scott RM, Burke DS, Hoke CH, Innis BL, Vaughn DW, 2003. Serotype-specific dengue virus circulation and dengue disease in Bangkok, Thailand from 1973 to 1999. Am J Trop Med Hyg 68: 191202.

    • Search Google Scholar
    • Export Citation
  • 19.

    Center for Vaccine Sciences, icddr,b, 2014. Seroprevalence of dengue virus infection in Dhaka, Bangladesh, 2012. Health Sci Bull 12: 16.

    • Search Google Scholar
    • Export Citation
  • 20.

    Paul RC, Rahman M, Gurley ES, Hossain MJ, Diorditsa S, Hasan AM, Banu SS, Alamgir A, Rahman MA, Sandhu H, Fischer M, Luby SP, 2011. A novel low-cost approach to estimate the incidence of Japanese encephalitis in the catchment area of three hospitals in Bangladesh. Am J Trop Med Hyg 85: 379385.

    • Search Google Scholar
    • Export Citation
 
 
 

 

 
 
 

 

 

 

 

 

 

Seasonal Distribution and Climatic Correlates of Dengue Disease in Dhaka, Bangladesh

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  • Section on Membrane and Cellular Biophysics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Child Health Research Foundation, Department of Microbiology, Dhaka Shishu Hospital, Dhaka, Bangladesh; Department of Microbiology, Popular Diagnostic Centre, Dhaka, Bangladesh; International Center for Diarrheal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh; Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Paris, France

Dengue has been regularly reported in Dhaka, Bangladesh, since a large outbreak in 2000. However, to date, we have limited information on the seasonal distribution of dengue disease and how case distribution correlates with climate. Here, we analyzed dengue cases detected at a private diagnostic facility in Dhaka during 2010–2014. We calculated Pearson cross-correlation coefficients to examine the relationship between the timing of cases and both rainfall and temperature. There were 2,334 cases diagnosed during the study period with 76% over the age of 15 years. Cases were reported in every month of the study; however, 90% of cases occurred between June and November. Increases in rainfall were correlated with increases in cases 2 months later (correlation of 0.7). The large proportion of adult cases is consistent with substantial population susceptibility and suggests Dhaka remains at risk for outbreaks. Although cases occurred year-round, public health preparedness should be focused during peak months.

Dengue is caused by infection with the dengue virus (DENV), a member of the genus Flavivirus and is transmitted by two principal mosquito vectors of the genus Aedes: Aedes aegypti and Aedes albopictus.1 It is estimated that about 400 million dengue infections occur each year in tropical and subtropical countries.1,2 There are four DENV serotypes, and a primary infection usually results in mild disease; however, reinfection with a different DENV serotype is more likely to result in dengue hemorrhagic fever, a more severe disease manifestation.2 Dengue incidence has been associated with variations in climate. Increased rainfall supports vector habitat availability, and high temperatures promote mosquito development.3 Dengue epidemics often occur seasonally, with more cases found during wetter and warmer months. However, the complex role of local immunity patterns and population structure on transmission means that the relationship between incidence and climate remains poorly understood and often differs across settings because of local climate heterogeneity, circulating DENV serotypes, and virus–host interactions.4 Dengue is largely a pediatric disease in much of southeast Asia, where it has circulated for over 60 years in countries such as Thailand, Vietnam, and the Philippines.57 The epidemiology of dengue in south Asia is less clear. The first report of dengue in Bangladesh was in 1964.1 Cases have been reported regularly in Dhaka, the capital of Bangladesh, since a large outbreak of dengue hemorrhagic fever in 20008; however, limited surveillance capabilities mean that we do not know if there exists year round transmission, nor which age groups are most affected by the disease. The objective of this study was to characterize the seasonality and age distribution of dengue cases and explore the climatic drivers of transmission.

Surveillance for dengue in Bangladesh is particularly difficult as public hospitals rarely have access to diagnostic kits so diagnosis usually relies on clinician assessments, which may be affected by underreporting or misdiagnosis for other febrile illnesses.9 However, dengue testing is routinely performed in the private health-care sector. Here, we analyzed data from Popular Diagnostic, one of the largest private laboratories in Dhaka.

Data consisted of de-identified dengue antibody test results, age and sex of individuals who were physician referred or self-referred for a dengue antibody test between February 2010 and December 2014. Samples were tested for dengue IgM and IgG antibodies using an immunochromatographic strip test (Bio Focus; Bio Focus Co., Ltd., Uiwang-si, Korea).10 The average cost per test was approximately US$10. To explore the correlation between climate and dengue cases, dengue cases were aggregated by month. Meteorological data on hourly temperature (°C) and amount of rainfall (mm) were obtained from the local Meteorological Department in Dhaka. We calculated average rainfall and temperature for each month of the study period. In addition, we calculated the number of days with any rain and the mean daily minimum temperature within each month. We then calculated Pearson cross-correlation coefficients between monthly case counts and each of these climate variables. The cross-correlations were calculated using the ccf function in the stats package in R (R Foundation for Statistical Computing, Vienna, Austria). Monthly lags of up to 6 months (in both positive and negative directions) were considered. The study was approved by the institutional review board of the International Center for Diarrheal Disease Research, Bangladesh.

Of 4,439 serum specimens tested, 2,334 had evidence of IgM antibodies, suggestive of recent dengue infection. Of these cases, 1,282 (55%) were male. Cases had a mean age of 28 years and ranged from under 1 year to 91 years old (Figure 1). Individuals who tested negative for dengue had a similar mean age of 25 years. Overall, 24% (95% confidence interval [CI]: 23%, 26%) of cases were under 15 years of age (Figure 1). We observed cases throughout the year, however, cases were seasonally distributed, with peak counts observed in August and September (Figure 2A); 90% of cases occurred between June and November. Correlation between rainfall and case counts peaked at a lag of 2 months (correlation of 0.70) (Figure 2B). Peak correlation with both mean and minimum temperature was also at a lag of 2 months (peak correlation of 0.5 for mean temperature and 0.6 for minimum temperature) (Figure 2C and Supplemental Figure 1). Peak correlation with number of days with any rain occurred at a time lag of 1 month (correlation of 0.71) (Supplemental Figure 1).

Figure 1.
Figure 1.

Age distribution of dengue cases for the period 2010–2014. Percentage of dengue cases in each age category over the entire study period.

Citation: The American Society of Tropical Medicine and Hygiene 94, 6; 10.4269/ajtmh.15-0846

Figure 2.
Figure 2.

Time series and cross-correlation plots of climatic variables and dengue cases in Dhaka, from 2010 to 2014. (A) Time series of the monthly mean temperature, rainfall, and dengue cases. (B) Cross-correlation plot of monthly dengue cases and rainfall. (C) Cross-correlation plot of monthly dengue cases and temperature. The x axis gives the number of lags per month, and the y axis gives the value of the correlation coefficient between −1 and 1. Dotted lines indicate the 95% confidence level.

Citation: The American Society of Tropical Medicine and Hygiene 94, 6; 10.4269/ajtmh.15-0846

We have shown that over this 5-year period, dengue cases increased during the monsoon season each year similar to what has previously been observed from reported cases in Dhaka.8 We found that peak case counts occurred 2 months after peak rainfall. These findings are similar to what has been reported for rainfall and mean temperature in Vietnam (lag 1–2 months).11 The seasonality of cases as well as the seasonality of rainfall and temperature were largely consistent across years (Figure 2A). Health-care providers should prepare for increased numbers of dengue cases in August and September. Given the similarity across years, we could not specifically assess whether significant changes in the timing of rainfall or temperature were associated with differences in case seasonality. However, given the potential role that temperature and rainfall have on the vector in particular, we could expect that large-scale changes in climate may change the seasonality of transmission. Despite a clear seasonal peak, cases were nevertheless observed year-round, consistent with sustained endemic transmission similar to the dengue dynamics observed in many countries in southeast Asia.1214 A previous study using reported cases in Dhaka from 2000 to 2010 detected only eight cases between January and May throughout the 10-year period.8 The case definition used in that study relied only on physician's clinical diagnosis without diagnostic testing. Our findings highlight the importance of systematic surveillance for diagnosed cases to characterize true seasonal patterns and further suggest that physicians should consider dengue as a differential diagnosis throughout the year.

Our data were obtained from a private diagnostic facility. We cannot assume that these individuals are representative of all dengue cases in Dhaka. Health-seeking behavior is typically determined by socioeconomic status (SES), disease severity, age, and gender.15 Specifically, low-SES individuals may be less likely to afford private health-care services.15 According to a 2010 national survey on household income and expenditure, the average monthly household income was approximately US$150.16 Therefore, many cases in Dhaka may not have been able to afford the cost ($10) of the test and the consultancy fee at a private laboratory. Nevertheless, these differences in health-care seeking behavior are unlikely to fully explain our finding that 76% of cases are over 15 years of age. A preponderance of adult cases is consistent with only recent sustained transmission of the virus. In settings where the virus has circulated for long periods, most individuals are immune by the time they reach adulthood.17 For example, the proportion of dengue cases over the age of 15 years in 2010 was 52% in Thailand and only 28% in the Philippines.5,6 Both countries have had endemic dengue circulation for decades.18 The first observed large-scale outbreak of dengue in Bangladesh was in 2000, far later than these countries, which also supports more recent endemic transmission. A seroprevalence study in 2012 found that 80% of individuals in Dhaka had evidence of historic infection with dengue19; however, as individuals can get infected more than once, this is not a true indicator of protection from disease. If dengue continues to circulate with a high force of infection in Dhaka, we can expect an increasing number of pediatric cases.

The cases in our study represent only a tiny proportion of all dengue cases in the city. We therefore cannot use these data to directly estimate the incidence of dengue in Dhaka. Even trends across years can be difficult to interpret due to variations in health-care seeking or changing population size and structure. However, the distribution of cases within any year is less likely to be affected by such secular trends and therefore would not impact our estimates of the seasonality of dengue and the association with climate. The sensitivity and specificity of the diagnostic assay were relatively high (sensitivity of 91.3% and specificity of 92%; www.biofocus.co.kr). Antibody cross-reactivity between dengue and other flaviviruses may occur. However, while Japanese encephalitis virus circulates in Bangladesh, it is largely restricted to rural areas.20 Cross-reactivity with other flaviviruses cannot be ruled out. Delays in health-care seeking may have led to the disappearance of IgM antibodies, which peak 2 weeks after fever onset and decline over the next 2–3 months, and therefore, the presence of false negatives is possible. However, the distribution of false-positive or false-negative cases in our dataset is unlikely to differ by time of year and therefore would not impact our characterization of the seasonal distribution of dengue.

In conclusion, these findings demonstrate that transmission of dengue occurs year-round, even during cooler, drier months. Public health preparedness should nevertheless be focused during peak months to help cope with potentially large influxes of patients. Public health surveillance systems can benefit from engaging private laboratories, especially where public sector access to diagnostics is limited.

ACKNOWLEDGMENTS

icddr,b acknowledges with gratitude the commitment of CDC to its research efforts. Henrik Salje would like to acknowledge funding from the NIH (grant no. R01AI102939-01A1). icddr,b is also grateful to the Governments of Bangladesh, Canada, Sweden, and the United Kingdom for providing core/unrestricted support.

  • 1.

    Sharmin S, Viennet E, Glass K, Harley D, 2015. The emergence of dengue in Bangladesh: epidemiology, challenges and future disease risk. Trans R Soc Trop Med Hyg 109: 619627.

    • Search Google Scholar
    • Export Citation
  • 2.

    Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, Drake JM, Brownstein JS, Hoen AG, Sankoh O, Myers MF, George DB, Jaenisch T, Wint GR, Simmons CP, Scott TW, Farrar JJ, Hay SI, 2013. The global distribution and burden of dengue. Nature 496: 504507.

    • Search Google Scholar
    • Export Citation
  • 3.

    Pham HV, Doan HT, Phan TT, Minh NN, 2011. Ecological factors associated with dengue fever in a Central Highlands province, Vietnam. BMC Infect Dis 11: 172.

    • Search Google Scholar
    • Export Citation
  • 4.

    Johansson MA, Cummings DA, Glass GE, 2009. Multiyear climate variability and dengue—El Nino southern oscillation, weather, and dengue incidence in Puerto Rico, Mexico, and Thailand: a longitudinal data analysis. PLoS Med 6: e1000168.

    • Search Google Scholar
    • Export Citation
  • 5.

    Limkittikul K, Brett J, L'Azou M, 2014. Epidemiological trends of dengue disease in Thailand (2000–2011): a systematic literature review. PLoS Negl Trop Dis 8: e3241.

    • Search Google Scholar
    • Export Citation
  • 6.

    Bravo L, Roque VG, Brett J, Dizon R, L'Azou M, 2014. Epidemiology of dengue disease in the Philippines (2000–2011): a systematic literature review. PLoS Negl Trop Dis 8: e3027.

    • Search Google Scholar
    • Export Citation
  • 7.

    Quang Ha D, Quan Huan T, 1997. Dengue activity in Vietnam and its control programme 1997–1998. Dengue Bull 21: 3543.

  • 8.

    Karim MN, Munshi SU, Anwar N, Alam MS, 2012. Climatic factors influencing dengue cases in Dhaka city: a model for dengue prediction. Indian J Med Res 136: 3239.

    • Search Google Scholar
    • Export Citation
  • 9.

    Sharmin S, Glass K, Viennet E, Harley D, 2015. Interaction of mean temperature and daily fluctuation influences dengue incidence in Dhaka, Bangladesh. PLoS Negl Trop Dis 9: e0003901.

    • Search Google Scholar
    • Export Citation
  • 10.

    Sang CT, Hoon LS, Cuzzubbo A, Devine P, 1998. Clinical evaluation of a rapid immunochromatographic test for the diagnosis of dengue virus infection. Clin Diagn Lab Immunol 5: 407409.

    • Search Google Scholar
    • Export Citation
  • 11.

    Cuong HQ, Hien NT, Duong TN, Phong TV, Cam NN, Farrar J, Nam VS, Thai KT, Horby P, 2011. Quantifying the emergence of dengue in Hanoi, Vietnam: 1998–2009. PLoS Negl Trop Dis 5: e1322.

    • Search Google Scholar
    • Export Citation
  • 12.

    Xuan Le TT, Van Hau P, Thu Do T, Toan Do TT, 2014. Estimates of meteorological variability in association with dengue cases in a coastal city in northern Vietnam: an ecological study. Glob Health Action 7: 23119.

    • Search Google Scholar
    • Export Citation
  • 13.

    Velasco JM, Alera MT, Ypil-Cardenas CA, Dimaano EM, Jarman RG, Chinnawirotpisan P, Thaisomboonsuk B, Yoon IK, Cummings DA, Mammen MP Jr, 2014. Demographic, clinical and laboratory findings among adult and pediatric patients hospitalized with dengue in the Philippines. Southeast Asian J Trop Med Public Health 45: 337345.

    • Search Google Scholar
    • Export Citation
  • 14.

    Campbell KM, Lin CD, Iamsirithaworn S, Scott TW, 2013. The complex relationship between weather and dengue virus transmission in Thailand. Am J Trop Med Hyg 89: 10661080.

    • Search Google Scholar
    • Export Citation
  • 15.

    Faruque LI, Zaman RU, Alamgir AS, Gurley ES, Haque R, Rahman M, Luby SP, 2012. Hospital-based prevalence of malaria and dengue in febrile patients in Bangladesh. Am J Trop Med Hyg 86: 5864.

    • Search Google Scholar
    • Export Citation
  • 16.

    Bangladesh Bureau of Statistics, Ministry of Planning, 2010. Report of the Household Income and Expenditure Survey 2010. Dhaka, Bangladesh: Bangladesh Bureau of Statistics, 27.

    • Search Google Scholar
    • Export Citation
  • 17.

    Bhatia R, Dash AP, Sunyoto T, 2013. Changing epidemiology of dengue in south-east Asia. WHO South East Asia J Public Health 2: 2327.

  • 18.

    Nisalak A, Endy TP, Nimmannitya S, Kalayanarooj S, Thisayakorn U, Scott RM, Burke DS, Hoke CH, Innis BL, Vaughn DW, 2003. Serotype-specific dengue virus circulation and dengue disease in Bangkok, Thailand from 1973 to 1999. Am J Trop Med Hyg 68: 191202.

    • Search Google Scholar
    • Export Citation
  • 19.

    Center for Vaccine Sciences, icddr,b, 2014. Seroprevalence of dengue virus infection in Dhaka, Bangladesh, 2012. Health Sci Bull 12: 16.

    • Search Google Scholar
    • Export Citation
  • 20.

    Paul RC, Rahman M, Gurley ES, Hossain MJ, Diorditsa S, Hasan AM, Banu SS, Alamgir A, Rahman MA, Sandhu H, Fischer M, Luby SP, 2011. A novel low-cost approach to estimate the incidence of Japanese encephalitis in the catchment area of three hospitals in Bangladesh. Am J Trop Med Hyg 85: 379385.

    • Search Google Scholar
    • Export Citation

Author Notes

* Address correspondence to Emily S. Gurley, Programme for Emerging Infections, icddr,b, 68 Shaheed Tajuddin Ahmed Sarani, Mohakhali, Dhaka 1212, Bangladesh. E-mail: egurley@icddrb.org

Financial support: This research study was funded by Centers for Disease Control and Prevention, Atlanta, under the cooperative agreement (grant no. 1U01GH001207-01).

Authors' addresses: Ivonne Morales, Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, and Section on Membrane and Cellular Biophysics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, E-mail: imorale1@jhu.edu. Henrik Salje, Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, and Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Paris, France, E-mail: hsalje1@jhu.edu. Samir Saha, Child Health Research Foundation, Department of Microbiology, Dhaka Shishu Hospital, Dhaka, Bangladesh, and Department of Microbiology, Popular Diagnostic Center, Dhaka, Bangladesh, E-mail: samir.sks@gmail.com. Emily S. Gurley, Programme on Emerging Infections, icddr,b, Dhaka, Bangladesh, and Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, E-mail: egurley@icddrb.org.

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