Search tips
Search criteria

Results 1-13 (13)

Clipboard (0)

Select a Filter Below

more »
Year of Publication
Document Types
author:("kenaf, eber")
1.  Household Transmission of Vibrio cholerae in Bangladesh 
Vibrio cholerae infections cluster in households. This study's objective was to quantify the relative contribution of direct, within-household exposure (for example, via contamination of household food, water, or surfaces) to endemic cholera transmission. Quantifying the relative contribution of direct exposure is important for planning effective prevention and control measures.
Methodology/Principal Findings
Symptom histories and multiple blood and fecal specimens were prospectively collected from household members of hospital-ascertained cholera cases in Bangladesh from 2001–2006. We estimated the probabilities of cholera transmission through 1) direct exposure within the household and 2) contact with community-based sources of infection. The natural history of cholera infection and covariate effects on transmission were considered. Significant direct transmission (p-value<0.0001) occurred among 1414 members of 364 households. Fecal shedding of O1 El Tor Ogawa was associated with a 4.9% (95% confidence interval: 0.9%–22.8%) risk of infection among household contacts through direct exposure during an 11-day infectious period (mean length). The estimated 11-day risk of O1 El Tor Ogawa infection through exposure to community-based sources was 2.5% (0.8%–8.0%). The corresponding estimated risks for O1 El Tor Inaba and O139 infection were 3.7% (0.7%–16.6%) and 8.2% (2.1%–27.1%) through direct exposure, and 3.4% (1.7%–6.7%) and 2.0% (0.5%–7.3%) through community-based exposure. Children under 5 years-old were at elevated risk of infection. Limitations of the study may have led to an underestimation of the true risk of cholera infection. For instance, available covariate data may have incompletely characterized levels of pre-existing immunity to cholera infection. Transmission via direct exposure occurring outside of the household was not considered.
Direct exposure contributes substantially to endemic transmission of symptomatic cholera in an urban setting. We provide the first estimate of the transmissibility of endemic cholera within prospectively-followed members of households. The role of direct transmission must be considered when planning cholera control activities.
Author Summary
Since John Snow's ground-breaking investigations of the devastating outbreaks in 19th-century London, cholera has been considered the quintessential waterborne human infection, transmitting via fecal contamination of environmental water sources. Recently, renewed interest has been paid to the potential importance of transmission through direct exposure within close-contact groups, such as, via fecal contamination of surfaces, food, or drinking water within households. Significant direct transmission of cholera within close contact groups would represent a new target for innovative prevention and control strategies. We estimated the probability of transmission 1) via direct contact within 364 urban households located in an endemic cholera setting (Dhaka, Bangladesh) and 2) via exposure to sources located outside of these households. In this setting we estimated a 4 to 8 percent probability of becoming infected with cholera via direct exposure within households in this setting versus a 2 to 3 percent likelihood of infection due to exposure to external sources over a comparable time period. Our results demonstrate that direct (within-household) transmission is a significant component of endemic cholera transmission, suggesting that biomedical and behavioral-modification interventions specifically targeting this mode of transmission could substantially reduce the cholera burden in this type of setting.
PMCID: PMC4238997  PMID: 25411971
2.  Clinical and Immunological Aspects of Post–Kala-Azar Dermal Leishmaniasis in Bangladesh 
We conducted active surveillance for kala-azar and post–kala-azar dermal leishmaniasis (PKDL) in a population of 24,814 individuals. Between 2002 and 2010, 1,002 kala-azar and 185 PKDL cases occurred. Median PKDL patient age was 12 years; 9% had no antecedent kala-azar. Cases per 10,000 person-years peaked at 90 for kala-azar (2005) and 28 for PKDL (2007). Cumulative PKDL incidence among kala-azar patients was 17% by 5 years. Kala-azar patients younger than 15 years were more likely than older patients to develop PKDL; no other risk factors were identified. The most common lesions were hypopigmented macules. Of 98 untreated PKDL patients, 48 (49%) patients had resolution, with median time of 19 months. Kala-azar patients showed elevated interferon-γ (IFNγ), tumor necrosis factor-α (TNFα), and interleukin 10 (IL-10). Matrix metalloproteinase 9 (MMP9) and MMP9/tissue inhibitor of matrix metalloproteinase-1 (TIMP1) ratio were significantly higher in PKDL patients than in other groups. PKDL is frequent in Bangladesh and poses a challenge to the current visceral leishmaniasis elimination initiative in the Indian subcontinent.
PMCID: PMC3741258  PMID: 23817330
3.  Nonparametric survival analysis of infectious disease data 
This paper develops nonparametric methods based on contact intervals for the analysis of infectious disease data. The contact interval from person i to person j is the time between the onset of infectiousness in i and infectious contact from i to j, where we define infectious contact as a contact sufficient to infect a susceptible individual. The hazard function of the contact interval distribution equals the hazard of infectious contact from i to j, so it provides a summary of the evolution of infectiousness over time. When who-infects-whom is observed, the Nelson-Aalen estimator produces an unbiased estimate of the cumulative hazard function of the contact interval distribution. When who-infects-whom is not observed, we use an EM algorithm to average the Nelson-Aalen estimates from all possible combinations of who-infected-whom consistent with the observed data. This converges to a nonparametric maximum likelihood estimate of the cumulative hazard function that we call the marginal Nelson-Aalen estimate. We study the behavior of these methods in simulations and use them to analyze household surveillance data from the 2009 influenza A(H1N1) pandemic.
PMCID: PMC3681432  PMID: 23772180
Chain-binomial models; Contact intervals; Generation intervals; Infectious disease; Nonparametric methods; Survival analysis
4.  Contact intervals, survival analysis of epidemic data, and estimation of R0 
Biostatistics (Oxford, England)  2010;12(3):548-566.
We argue that the time from the onset of infectiousness to infectious contact, which we call the “contact interval,” is a better basis for inference in epidemic data than the generation or serial interval. Since contact intervals can be right censored, survival analysis is the natural approach to estimation. Estimates of the contact interval distribution can be used to estimate R0 in both mass-action and network-based models. We apply these methods to 2 data sets from the 2009 influenza A(H1N1) pandemic.
PMCID: PMC3114649  PMID: 21071607
Basic reproductive number (R0); Epidemic data; Generation intervals; Survival analysis
5.  The Global Transmission and Control of Influenza 
PLoS ONE  2011;6(5):e19515.
New strains of influenza spread around the globe via the movement of infected individuals. The global dynamics of influenza are complicated by different patterns of influenza seasonality in different regions of the world. We have released an open-source stochastic mathematical model of the spread of influenza across 321 major, strategically located cities of the world. Influenza is transmitted between cities via infected airline passengers. Seasonality is simulated by increasing the transmissibility in each city at the times of the year when influenza has been observed to be most prevalent. The spatiotemporal spread of pandemic influenza can be understood through clusters of global transmission and links between them, which we identify using the epidemic percolation network (EPN) of the model. We use the model to explain the observed global pattern of spread for pandemic influenza A(H1N1) 2009–2010 (pandemic H1N1 2009) and to examine possible global patterns of spread for future pandemics depending on the origin of pandemic spread, time of year of emergence, and basic reproductive number (). We also use the model to investigate the effectiveness of a plausible global distribution of vaccine for various pandemic scenarios. For pandemic H1N1 2009, we show that the biggest impact of vaccination was in the temperate northern hemisphere. For pandemics starting in the temperate northern hemisphere in May or April, vaccination would have little effect in the temperate southern hemisphere and a small effect in the tropics. With the increasing interconnectedness of the world's population, we must take a global view of infectious disease transmission. Our open-source, computationally simple model can help public health officials plan for the next pandemic as well as deal with interpandemic influenza.
PMCID: PMC3089626  PMID: 21573121
6.  Epidemic Percolation Networks, Epidemic Outcomes, and Interventions 
Epidemic percolation networks (EPNs) are directed random networks that can be used to analyze stochastic “Susceptible-Infectious-Removed” (SIR) and “Susceptible-Exposed-Infectious-Removed” (SEIR) epidemic models, unifying and generalizing previous uses of networks and branching processes to analyze mass-action and network-based S(E)IR models. This paper explains the fundamental concepts underlying the definition and use of EPNs, using them to build intuition about the final outcomes of epidemics. We then show how EPNs provide a novel and useful perspective on the design of vaccination strategies.
PMCID: PMC3062991  PMID: 21437002
7.  The Transmissibility and Control of Pandemic Influenza A (H1N1) Virus 
Science (New York, N.Y.)  2009;326(5953):729-733.
Pandemic influenza A (H1N1) 2009 (pandemic H1N1) is spreading throughout the planet. It has become the dominant strain in the southern hemisphere, where the influenza season is underway. Here, based on reported case clusters in the USA, we estimate the household secondary attack rate for pandemic H1N1 to be 27.3% (95% CI: 12.2%–50.5%). From a school outbreak, we estimate a school child infects 2.4 (95% CI: 1.8–3.2) other children within the school. We estimate the basic reproductive number, R0, to range from 1.3–1.7 and the generation interval to range from 2.6–3.2 days. We use a simulation model to evaluate the effectiveness of vaccination strategies in the USA for the Fall, 2009. If vaccine were available soon enough, vaccination of children, followed by adults, reaching 70% overall coverage, in addition to high risk and essential workforce groups, could mitigate a severe epidemic.
PMCID: PMC2880578  PMID: 19745114
8.  Causes of Early Childhood Deaths in Urban Dhaka, Bangladesh 
PLoS ONE  2009;4(12):e8145.
Data on causes of early childhood death from low-income urban areas are limited. The nationally representative Bangladesh Demographic and Health Survey 2007 estimates 65 children died per 1,000 live births. We investigated rates and causes of under-five deaths in an urban community near two large pediatric hospitals in Dhaka, Bangladesh and evaluated the impact of different recall periods. We conducted a survey in 2006 for 6971 households and a follow up survey in 2007 among eligible remaining households or replacement households. The initial survey collected information for all children under five years old who died in the previous year; the follow up survey on child deaths in the preceding five years. We compared mortality rates based on 1-year recall to the 4 years preceding the most recent 1 year. The initial survey identified 58 deaths among children <5 years in the preceding year. The follow up survey identified a mean 53 deaths per year in the preceding five years (SD±7.3). Under-five mortality rate was 34 and neonatal mortality was 15 per thousand live births during 2006–2007. The leading cause of under-five death was respiratory infections (22%). The mortality rates among children under 4 years old for the two time periods (most recent 1-year recall and the 4 years preceding the most recent 1 year) were similar (36 versus 32). The child mortality in urban Dhaka was substantially lower than the national rate. Mortality rates were not affected by recall periods between 1 and 5 years.
PMCID: PMC2779865  PMID: 19997507
9.  Recurrent Zoonotic Transmission of Nipah Virus into Humans, Bangladesh, 2001–2007 
Emerging Infectious Diseases  2009;15(8):1229-1235.
More than half of identified cases result from person-to-person transmission.
Human Nipah outbreaks recur in a specific region and time of year in Bangladesh. Fruit bats are the reservoir host for Nipah virus. We identified 23 introductions of Nipah virus into human populations in central and northwestern Bangladesh from 2001 through 2007. Ten introductions affected multiple persons (median 10). Illness onset occurred from December through May but not every year. We identified 122 cases of human Nipah infection. The mean age of case-patients was 27 years; 87 (71%) died. In 62 (51%) Nipah virus–infected patients, illness developed 5–15 days after close contact with another Nipah case-patient. Nine (7%) Nipah case-patients transmitted virus to others. Nipah case-patients who had difficulty breathing were more likely than those without respiratory difficulty to transmit Nipah (12% vs. 0%, p = 0.03). Although a small minority of infected patients transmit Nipah virus, more than half of identified cases result from person-to-person transmission. Interventions to prevent virus transmission from bats to humans and from person to person are needed.
PMCID: PMC2815955  PMID: 19751584
Nipah virus; Bangladesh; disease transmission; respiratory tract infections; viruses; zoonoses; Pteropus; research
10.  Generation interval contraction and epidemic data analysis 
Mathematical biosciences  2008;213(1):71-79.
The generation interval is the time between the infection time of an infected person and the infection time of his or her infector. Probability density functions for generation intervals have been an important input for epidemic models and epidemic data analysis. In this paper, we specify a general stochastic SIR epidemic model and prove that the mean generation interval decreases when susceptible persons are at risk of infectious contact from multiple sources. The intuition behind this is that when a susceptible person has multiple potential infectors, there is a “race” to infect him or her in which only the first infectious contact leads to infection. In an epidemic, the mean generation interval contracts as the prevalence of infection increases. We call this global competition among potential infectors. When there is rapid transmission within clusters of contacts, generation interval contraction can be caused by a high local prevalence of infection even when the global prevalence is low. We call this local competition among potential infectors. Using simulations, we illustrate both types of competition. Finally, we show that hazards of infectious contact can be used instead of generation intervals to estimate the time course of the effective reproductive number in an epidemic. This approach leads naturally to partial likelihoods for epidemic data that are very similar to those that arise in survival analysis, opening a promising avenue of methodological research in infectious disease epidemiology.
PMCID: PMC2365921  PMID: 18394654
11.  Network-based analysis of stochastic SIR epidemic models with random and proportionate mixing 
Journal of theoretical biology  2007;249(4):706-722.
In this paper, we outline the theory of epidemic percolation networks and their use in the analysis of stochastic SIR epidemic models on undirected contact networks. We then show how the same theory can be used to analyze stochastic SIR models with random and proportionate mixing. The epidemic percolation networks for these models are purely directed because undirected edges disappear in the limit of a large population. In a series of simulations, we show that epidemic percolation networks accurately predict the mean outbreak size and probability and final size of an epidemic for a variety of epidemic models in homogeneous and heterogeneous populations. Finally, we show that epidemic percolation networks can be used to re-derive classical results from several different areas of infectious disease epidemiology. In an appendix, we show that an epidemic percolation network can be defined for any time-homogeneous stochastic SIR model in a closed population and prove that the distribution of outbreak sizes given the infection of any given node in the SIR model is identical to the distribution of its out-component sizes in the corresponding probability space of epidemic percolation networks. We conclude that the theory of percolation on semi-directed networks provides a very general framework for the analysis of stochastic SIR models in closed populations.
PMCID: PMC2186204  PMID: 17950362
12.  Second look at the spread of epidemics on networks 
In an important paper, M.E.J. Newman claimed that a general network-based stochastic Susceptible-Infectious-Removed (SIR) epidemic model is isomorphic to a bond percolation model, where the bonds are the edges of the contact network and the bond occupation probability is equal to the marginal probability of transmission from an infected node to a susceptible neighbor. In this paper, we show that this isomorphism is incorrect and define a semi-directed random network we call the epidemic percolation network that is exactly isomorphic to the SIR epidemic model in any finite population. In the limit of a large population, (i) the distribution of (self-limited) outbreak sizes is identical to the size distribution of (small) out-components, (ii) the epidemic threshold corresponds to the phase transition where a giant strongly-connected component appears, (iii) the probability of a large epidemic is equal to the probability that an initial infection occurs in the giant in-component, and (iv) the relative final size of an epidemic is equal to the proportion of the network contained in the giant out-component. For the SIR model considered by Newman, we show that the epidemic percolation network predicts the same mean outbreak size below the epidemic threshold, the same epidemic threshold, and the same final size of an epidemic as the bond percolation model. However, the bond percolation model fails to predict the correct outbreak size distribution and probability of an epidemic when there is a nondegenerate infectious period distribution. We confirm our findings by comparing predictions from percolation networks and bond percolation models to the results of simulations. In an appendix, we show that an isomorphism to an epidemic percolation network can be defined for any time-homogeneous stochastic SIR model.
PMCID: PMC2215389  PMID: 17930312
13.  Foodborne Transmission of Nipah Virus, Bangladesh 
Emerging Infectious Diseases  2006;12(12):1888-1894.
TOC summary line: Nipah virus was likely transmitted from fruit bats to humans by drinking fresh date palm sap.
We investigated an outbreak of encephalitis in Tangail District, Bangladesh. We defined case-patients as persons from the outbreak area in whom fever developed with new onset of seizures or altered mental status from December 15, 2004, through January 31, 2005. Twelve persons met the definition; 11 (92%) died. Serum specimens were available from 3; 2 had immunoglobulin M antibodies against Nipah virus by capture enzyme immunoassay. We enrolled 11 case-patients and 33 neighborhood controls in a case-control study. The only exposure significantly associated with illness was drinking raw date palm sap (64% among case-patients vs. 18% among controls, odds ratio [OR] 7.9, p = 0.01). Fruit bats (Pteropus giganteus) are a nuisance to date palm sap collectors because the bats drink from the clay pots used to collect the sap at night. This investigation suggests that Nipah virus was transmitted from P. giganteus to persons through drinking fresh date palm sap.
PMCID: PMC3291367  PMID: 17326940
Nipah Virus; Bangladesh; Encephalitis; Chiroptera; Epidemiology; Disease Outbreaks; Research

Results 1-13 (13)