Of the seven known species of human retroviruses only one, human T-cell lymphotropic virus type 4 (HTLV-4), lacks a known animal reservoir. We report the largest screening for simian T-cell lymphotropic virus (STLV-4) to date in a wide range of captive and wild non-human primate (NHP) species from Cameroon. Among the 681 wild and 426 captive NHPs examined, we detected STLV-4 infection only among gorillas by using HTLV-4-specific quantitative polymerase chain reaction. The large number of samples analyzed, the diversity of NHP species examined, the geographic distribution of infected animals relative to the known HTLV-4 case, as well as detailed phylogenetic analyses on partial and full genomes, indicate that STLV-4 is endemic to gorillas, and that rather than being an ancient virus among humans, HTLV-4 emerged from a gorilla reservoir, likely through the hunting and butchering of wild gorillas. Our findings shed further light on the importance of gorillas as keystone reservoirs for the evolution and emergence of human infectious diseases and provide a clear course for preventing HTLV-4 emergence through management of human contact with wild gorillas, the development of improved assays for HTLV-4/STLV-4 detection and the ongoing monitoring of STLV-4 among gorillas and for HTLV-4 zoonosis among individuals exposed to gorilla populations.
gorilla; human T-lymphotropic virus; primate; retrovirus; simian T-lymphotropic virus; zoonoses
Mathematical and computational models provide valuable tools that help public health planners to evaluate competing health interventions, especially for novel circumstances that cannot be examined through observational or controlled studies, such as pandemic influenza. The spread of diseases like influenza depends on the mixing patterns within the population, and these mixing patterns depend in part on local factors including the spatial distribution and age structure of the population, the distribution of size and composition of households, employment status and commuting patterns of adults, and the size and age structure of schools. Finally, public health planners must take into account the health behavior patterns of the population, patterns that often vary according to socioeconomic factors such as race, household income, and education levels.
FRED (a Framework for Reconstructing Epidemic Dynamics) is a freely available open-source agent-based modeling system based closely on models used in previously published studies of pandemic influenza. This version of FRED uses open-access census-based synthetic populations that capture the demographic and geographic heterogeneities of the population, including realistic household, school, and workplace social networks. FRED epidemic models are currently available for every state and county in the United States, and for selected international locations.
State and county public health planners can use FRED to explore the effects of possible influenza epidemics in specific geographic regions of interest and to help evaluate the effect of interventions such as vaccination programs and school closure policies. FRED is available under a free open source license in order to contribute to the development of better modeling tools and to encourage open discussion of modeling tools being used to evaluate public health policies. We also welcome participation by other researchers in the further development of FRED.
Pandemic influenza; Simulator; Agent-based model; Synthetic population; Influenza modeling
Dengue, a mosquito-borne virus of humans, infects over 50 million people annually. Infection with any of the four dengue serotypes induces protective immunity to that serotype, but does not confer long-term protection against infection by other serotypes. The immunological interactions between serotypes are of central importance in understanding epidemiological dynamics and anticipating the impact of dengue vaccines. We analysed a 38-year time series with 12 197 serotyped dengue infections from a hospital in Bangkok, Thailand. Using novel mechanistic models to represent different hypothesized immune interactions between serotypes, we found strong evidence that infection with dengue provides substantial short-term cross-protection against other serotypes (approx. 1–3 years). This is the first quantitative evidence that short-term cross-protection exists since human experimental infection studies performed in the 1950s. These findings will impact strategies for designing dengue vaccine studies, future multi-strain modelling efforts, and our understanding of evolutionary pressures in multi-strain disease systems.
dengue; infectious disease modelling; cross-protection; time-series models
Since states’ public health systems differ as to pandemic preparedness, this study explored whether such heterogeneity among states could affect the nation’s overall influenza rate.
The CDC produced a uniform set of scores on a 100-point scale from its 2008 national evaluation of state preparedness to distribute materiel from the Strategic National Stockpile (SNS). This study used these SNS scores to represent each state’s relative preparedness to distribute influenza vaccine in a timely manner and assumed that “optimal” vaccine distribution would reach at least 35% of the state’s population within 4 weeks. The scores were used to determine the timing of vaccine distribution for each state: each 10-point decrement of score below 90 added an additional delay increment to the distribution time.
Setting and Participants
A large-scale agent-based computational model simulated an influenza pandemic in the U.S. population. In this synthetic population each individual or agent had an assigned household, age, workplace or school destination, daily commute, and domestic inter-city air travel patterns.
Main Outcome Measures
Simulations compared influenza case rates both nationally and at the state level under three scenarios: no vaccine distribution (baseline), optimal vaccine distribution in all states, and vaccine distribution time modified according to state-specific SNS score.
Between optimal and SNS-modified scenarios, attack rates rose not only in low-scoring states but also in high-scoring states, demonstrating an inter-state spread of infections. Influenza rates were sensitive to variation of the SNS-modified scenario (delay increments of 1-day versus 5-days), but the inter-state effect remained.
The effectiveness of a response activity such as vaccine distribution could benefit from national standards and preparedness funding allocated in part to minimize inter-state disparities.
pandemics; preparedness; computational modeling; public health systems
Widespread avoidance of Measles-Mumps-Rubella vaccination (MMR), with a consequent increase in the incidence of major measles outbreaks, demonstrates that the effectiveness of vaccination programs can be thwarted by the public misperceptions of vaccine risk. By coupling game theory and epidemic models, we examine vaccination choice among populations stratified into two behavioral groups: vaccine skeptics and vaccine believers. The two behavioral groups are assumed to be heterogeneous with respect to their perceptions of vaccine and infection risks. We demonstrate that the pursuit of self-interest among vaccine skeptics often leads to vaccination levels that are suboptimal for a population, even if complete coverage is achieved among vaccine believers. The demand for measles vaccine across populations driven by individual self-interest was found to be more sensitive to the proportion of vaccine skeptics than to the extent to which vaccine skeptics misperceive the risk of vaccine. Furthermore, as the number of vaccine skeptics increases, the probability of infection among vaccine skeptics increases initially, but it decreases once the vaccine skeptics begin receiving the vaccination, if both behavioral groups are vaccinated according to individual self-interest. Our results show that the discrepancy between the coverages of measles vaccine that are driven by self-interest and those driven by population interest becomes larger when the cost of vaccination increases. This research illustrates the importance of public education on vaccine safety and infection risk in order to maintain vaccination levels that are sufficient to maintain herd immunity.
measles; game theory; epidemiological model; vaccine
RNA aptamers that bind the reverse transcriptase (RT) of human immunodeficiency virus (HIV) compete with nucleic acid primer/template for access to RT, inhibit RT enzymatic activity in vitro, and suppress viral replication when expressed in human cells. Numerous pseudoknot aptamers have been identified by sequence analysis, but relatively few have been confirmed experimentally. In this work, a screen of nearly 100 full-length and >60 truncated aptamer transcripts established the predictive value of the F1Pk and F2Pk pseudoknot signature motifs. The screen also identified a new, nonpseudoknot motif with a conserved unpaired UCAA element. High-throughput sequence (HTS) analysis identified 181 clusters capable of forming this novel element. Comparative sequence analysis, enzymatic probing and RT inhibition by aptamer variants established the essential requirements of the motif, which include two conserved base pairs (AC/GU) on the 5′ side of the unpaired UCAA. Aptamers in this family inhibit RT in primer extension assays with IC50 values in the low nmol/l range, and they suppress viral replication with a potency that is comparable with that of previously studied aptamers. All three known anti-RT aptamer families (pseudoknots, the UCAA element, and the recently described “(6/5)AL” motif) are therefore suitable for developing aptamer-based antiviral gene therapies.
RNA aptamer; antiviral gene therapy; high-throughput sequencing; HIV; reverse transcriptase
The chemical strategies used by ribozymes to enhance reaction rates are revealed in part from their metal ion and pH requirements. We find that kinase ribozyme K28(1-77)C, in contrast with previously characterized kinase ribozymes, requires Cu2+ for optimal catalysis of thiophosphoryl transfer from GTPγS. Phosphoryl transfer from GTP is greatly reduced in the absence of Cu2+, indicating a specific catalytic role independent of any potential interactions with the GTPγS thiophosphoryl group. In-line probing and ATPγS competition both argue against direct Cu2+ binding by RNA; rather, these data establish that Cu2+ enters the active site within a Cu2+•GTPγS or Cu2+•GTP chelation complex, and that Cu2+•nucleobase interactions further enforce Cu2+ selectivity and position the metal ion for Lewis acid catalysis. Replacing Mg2+ with [Co(NH3)6]3+ significantly reduced product yield, but not kobs, indicating that the role of inner-sphere Mg2+ coordination is structural rather than catalytic. Replacing Mg2+ with alkaline earths of increasing ionic radii (Ca2+, Sr2+ and Ba2+) gave lower yields and approximately linear rates of product accumulation. Finally, we observe that reaction rates increased with pH in log-linear fashion with an apparent pKa = 8.0 ± 0.1, indicating deprotonation in the rate-limiting step.
Pathogenesis studies of SIV infection have not been performed to date in wild monkeys due to difficulty in collecting and storing samples on site and the lack of analytical reagents covering the extensive SIV diversity. We performed a large scale study of molecular epidemiology and natural history of SIVagm infection in 225 free-ranging AGMs from multiple locations in South Africa. SIV prevalence (established by sequencing pol, env, and gag) varied dramatically between infant/juvenile (7%) and adult animals (68%) (p<0.0001), and between adult females (78%) and males (57%). Phylogenetic analyses revealed an extensive genetic diversity, including frequent recombination events. Some AGMs harbored epidemiologically linked viruses. Viruses infecting AGMs in the Free State, which are separated from those on the coastal side by the Drakensberg Mountains, formed a separate cluster in the phylogenetic trees; this observation supports a long standing presence of SIV in AGMs, at least from the time of their speciation to their Plio-Pleistocene migration. Specific primers/probes were synthesized based on the pol sequence data and viral loads (VLs) were quantified. VLs were of 104–106 RNA copies/ml, in the range of those observed in experimentally-infected monkeys, validating the experimental approaches in natural hosts. VLs were significantly higher (107–108 RNA copies/ml) in 10 AGMs diagnosed as acutely infected based on SIV seronegativity (Fiebig II), which suggests a very active transmission of SIVagm in the wild. Neither cytokine levels (as biomarkers of immune activation) nor sCD14 levels (a biomarker of microbial translocation) were different between SIV-infected and SIV-uninfected monkeys. This complex algorithm combining sequencing and phylogeny, VL quantification, serology, and testing of surrogate markers of microbial translocation and immune activation permits a systematic investigation of the epidemiology, viral diversity and natural history of SIV infection in wild African natural hosts.
We simultaneously assessed, for the first time in a natural host, the epidemiology, diversity and natural history of SIVagmVer infection in wild vervet populations from South Africa. We report that African green monkeys (AGMs) have likely been infected with SIVagm for a long period, ranging from the time of their speciation to Plio-Pleistocene migrations, refuting previous molecular clock calculations suggesting SIVagm to be of recent occurrence. As a result of virus-host coadaptation, SIVagmVer infection is characterized by a lack of disease progression in spite of robust viral replication. We show that very active SIVagm transmission in adult AGMs contrasts with a very limited transmission to their offspring, in spite of massive exposure to SIVagm both in utero and through breastfeeding. The observation that some AGMs remain uninfected in spite of life-long exposure to SIVagm identifies wild vervets as an acceptable animal model for the exposed uninfected individuals, which can be used to identify correlates of resistance to HIV/SIV infection.
Systematic evolution of ligands through exponential enrichment (SELEX) is a well-established method for generating nucleic acid populations that are enriched for specified functions. High-throughput sequencing (HTS) enhances the power of comparative sequence analysis to reveal details of how RNAs within these populations recognize their targets. We used HTS analysis to evaluate RNA populations selected to bind type I human immunodeficiency virus reverse transcriptase (RT). The populations are enriched in RNAs of independent lineages that converge on shared motifs and in clusters of RNAs with nearly identical sequences that share common ancestry. Both of these features informed inferences of the secondary structures of enriched RNAs, their minimal structural requirements and their stabilities in RT-aptamer complexes. Monitoring population dynamics in response to increasing selection pressure revealed RNA inhibitors of RT that are more potent than the previously identified pseudoknots. Improved potency was observed for inhibition of both purified RT in enzymatic assays and viral replication in cell-based assays. Structural and functional details of converged motifs that are obscured by simple consensus descriptions are also revealed by the HTS analysis. The approach presented here can readily be generalized for the efficient and systematic post-SELEX development of aptamers for down-stream applications.
States’ pandemic influenza plans and school closure statutes are intended to guide state and local officials, but most faced a great deal of uncertainty during the 2009 influenza H1N1 epidemic. Questions remained about whether, when, and for how long to close schools and about which agencies and officials had legal authority over school closures.
This study began with analysis of states’ school-closure statutes and pandemic influenza plans to identify the variations among them. An agent-based model of one state was used to represent as constants a population’s demographics, commuting patterns, work and school attendance, and community mixing patterns while repeated simulations explored the effects of variations in school closure authority, duration, closure thresholds, and reopening criteria.
The results show no basis on which to justify statewide rather than school-specific or community-specific authority for school closures. Nor do these simulations offer evidence to require school closures promptly at the earliest stage of an epidemic. More important are criteria based on monitoring of local case incidence and on authority to sustain closure periods sufficiently to achieve epidemic mitigation.
This agent-based simulation suggests several ways to improve statutes and influenza plans. First, school closure should remain available to state and local authorities as an influenza mitigation strategy. Second, influenza plans need not necessarily specify the threshold for school closures but should clearly define provisions for early and ongoing local monitoring. Finally, school closure authority may be exercised at the statewide or local level, so long as decisions are informed by monitoring incidence in local communities and schools.
Laboratory-based evidence is lacking regarding the efficacy of non-pharmaceutical interventions such as alcohol-based hand sanitizer and respiratory hygiene to reduce the spread of influenza.
The Pittsburgh Influenza Prevention Project was a cluster-randomized trial conducted in ten Pittsburgh, PA elementary schools during the 2007-2008 influenza season. Children in five intervention schools received training in hand and respiratory hygiene, and were provided and encouraged to use hand sanitizer regularly. Children in five schools acted as controls. Children with influenza-like illness were tested for influenza A and B by RT-PCR.
3360 children participated. Using RT-PCR, 54 cases of influenza A and 50 cases of influenza B were detected. We found no significant effect of the intervention on the primary study outcome of all laboratory confirmed influenza cases (IRR 0.81 95% CI 0.54, 1.23). However, we did find statistically significant differences in protocol-specified ancillary outcomes. Children in intervention schools had significantly fewer laboratory-confirmed influenza A infections than children in control schools, with an adjusted IRR of 0.48 (95% CI 0.26, 0.87). Total absent episodes were also significantly lower among the intervention group than among the control group; adjusted IRR 0.74 (95% CI 0.56, 0.97).
Non-pharmaceutical interventions (respiratory hygiene education and the regular use of hand sanitizer) did not reduce total laboratory confirmed influenza. However the interventions did reduce school total absence episodes by 26% and laboratory-confirmed influenza A infections by 52%. Our results suggest that NPIs can be an important adjunct to influenza vaccination programs to reduce the number of influenza A infections among children.
Influenza; Non-pharmaceutical Interventions; School-aged Children; Randomized Controlled Trial; Hand Sanitizer; Absence Surveillance; Laboratory Testing
Analysis of historical data has strongly shaped our understanding of the epidemiology of pandemic influenza and informs analysis of current and future epidemics. Here, the authors analyzed previously unpublished documents from a large household survey of the “Spanish” H1N1 influenza pandemic, conducted in 1918, for the first time quantifying influenza transmissibility at the person-to-person level during that most lethal of pandemics. The authors estimated a low probability of person-to-person transmission relative to comparable estimates from seasonal influenza and other directly transmitted infections but similar to recent estimates from the 2009 H1N1 pandemic. The authors estimated a very low probability of asymptomatic infection, a previously unknown parameter for this pandemic, consistent with an unusually virulent virus. The authors estimated a high frequency of prior immunity that they attributed to a largely unreported influenza epidemic in the spring of 1918 (or perhaps to cross-reactive immunity). Extrapolating from this finding, the authors hypothesize that prior immunity partially protected some populations from the worst of the fall pandemic and helps explain differences in attack rates between populations. Together, these analyses demonstrate that the 1918 influenza virus, though highly virulent, was only moderately transmissible and thus in a modern context would be considered controllable.
disease transmission, infectious; epidemics; history of medicine; influenza, human; Orthomyxoviridae; pandemics; virulence
Understanding the mechanism of influenza spread across multiple geographic scales is not complete. While the mechanism of dissemination across regions and states of the United States has been described, understanding the determinants of dissemination between counties has not been elucidated. The paucity of high resolution spatial-temporal influenza incidence data to evaluate disease structure is often not available.
Methodology and Findings
We report on the underlying relationship between the spread of influenza and human movement between counties of one state. Significant synchrony in the timing of epidemics exists across the entire state and decay with distance (regional correlation = 62%). Synchrony as a function of population size display evidence of hierarchical spread with more synchronized epidemics occurring among the most populated counties. A gravity model describing movement between two populations is a stronger predictor of influenza spread than adult movement to and from workplaces suggesting that non-routine and leisure travel drive local epidemics.
These findings highlight the complex nature of influenza spread across multiple geographic scales.
We investigated whether introducing the rotavirus and pneumococcal vaccines, which are greatly needed in West Africa, would overwhelm existing supply chains (i.e., the series of steps required to get a vaccine from the manufacturers to the target population) in Niger.
As part of the Bill and Melinda Gates Foundation–funded Vaccine Modeling Initiative, we developed a computational model to determine the impact of introducing these new vaccines to Niger’s Expanded Program on Immunization vaccine supply chain.
Introducing either the rotavirus vaccine or the 7-valent pneumococcal conjugate vaccine could overwhelm available storage and transport refrigerator space, creating bottlenecks that would prevent the flow of vaccines down to the clinics. As a result, the availability of all World Health Organization Expanded Program on Immunization vaccines to patients might decrease from an average of 69% to 28.2% (range=10%–51%). Addition of refrigerator and transport capacity could alleviate this bottleneck.
Our results suggest that the effects on the vaccine supply chain should be considered when introducing a new vaccine and that computational models can help assess evolving needs and prevent problems with vaccine delivery.
In a low or middle income country, determining the correct number of routine vaccines to order at a health clinic can be difficult, especially given the variability in the number of patients arriving minimal vaccination days and resource (e.g., information technology and refrigerator space) constraints. We developed a spreadsheet model to determine the potential impact of different ordering policies, basing orders on the arrival rates seen in the previous 1, 3, 6, or 12 sessions, or on long-term historical averages (where these might be available) along with various buffer stock levels (range: 5% to 50%). Experiments varied patient arrival rates (mean range: 1–30 per session), arrival rate distributions (Poisson, Normal, and Uniform) and vaccine vial sizes (range: one-dose to ten-dose vials). It was found that when the number of doses per vial is small and the expected number of patients is low, the ordering policy has a more significant impact on the ability to meet demand. Using data from more prior sessions to determine arrival rates generally equates to a better ability to meet demand, although the marginal benefit is relatively small after more than 6 sessions are averaged. As expected, the addition of more buffer is helpful in obtaining better performance; however, this advantage also has notable diminishing returns. In general, the long-term demand rate, the vial sizes of the vaccines used and the method of determining the patient arrival rate all have an effect on the ability of a clinic to maximize the demand that is met.
Since hospitals in a region often share patients, an outbreak of methicillin-resistant Staphylococcus aureus (MRSA) infection in one hospital could affect other hospitals.
Using extensive data collected from Orange County (OC), California, we developed a detailed agent-based model to represent patient movement among all OC hospitals. Experiments simulated MRSA outbreaks in various wards, institutions, and regions. Sensitivity analysis varied lengths of stay, intraward transmission coefficients (β), MRSA loss rate, probability of patient transfer or readmission, and time to readmission.
Each simulated outbreak eventually affected all of the hospitals in the network, with effects depending on the outbreak size and location. Increasing MRSA prevalence at a single hospital (from 5% to 15%) resulted in a 2.9% average increase in relative prevalence at all other hospitals (ranging from no effect to 46.4%). Single-hospital intensive care unit outbreaks (modeled increase from 5% to 15%) caused a 1.4% average relative increase in all other OC hospitals (ranging from no effect to 12.7%).
MRSA outbreaks may rarely be confined to a single hospital but instead may affect all of the hospitals in a region. This suggests that prevention and control strategies and policies should account for the interconnectedness of health care facilities.
As history has demonstrated, post-approval obstacles can impede a vaccine’s use and potentially lead to its withdrawal. Addressing these potential obstacles when changes in a vaccine’s technology can still be easily made may improve a vaccine’s chances of success. Augmented vaccine target product profiles (TPPs) can help vaccine scientists better understand and anticipate these obstacles and galvanize conversations among various vaccine stakeholders (e.g., scientists, marketers, business development managers, policy makers, public health officials, health care workers, third party payors, etc.) earlier in a vaccine’s development.
Vaccines; Development; Target product profiles; Market
When influenza vaccines are in short supply, allocating vaccines equitably among different jurisdictions can be challenging. But justice is not the only reason to ensure that poorer counties have the same access to influenza vaccines as do wealthier ones. Using a detailed computer simulation model of the Washington, D.C., metropolitan region, we found that limiting or delaying vaccination of residents of poorer counties could raise the total number of influenza infections and the number of new infections per day at the peak of an epidemic throughout the region—even in the wealthier counties that had received more timely and abundant vaccine access. Among other underlying reasons, poorer counties tend to have high-density populations and more children and other higher-risk people per household, resulting in more interactions and both increased transmission of influenza and greater risk for worse influenza outcomes. Thus, policy makers across the country, in poor and wealthy areas alike, have an incentive to ensure that poorer residents have equal access to vaccines.
Phosphoryl transfer onto backbone hydroxyls is a recognized catalytic activity of nucleic acids. We find that kinase ribozyme K28 possesses an unusually complex active site that promotes (thio)phosphorylation of two residues widely separated in primary sequence. After allowing the ribozyme to radiolabel itself by phosphoryl transfer from [γ-32P]GTP, DNAzyme-mediated cleavage yielded two radiolabeled cleavage fragments, indicating phosphorylation sites within each of the two cleavage fragments. These sites were mapped by alkaline digestion and primer extension pausing. Enzymatic digestion and mutational analysis identified nucleotides important for activity and established the active structure as being a constrained pseudoknot with unusual connectivity that may juxtapose the two reactive sites. Nuclease sensitivities for nucleotides near the pseudoknot core were altered in the presence of GTPγS, indicating donor-induced folding. The 5′ target site was more strongly favored in full-length ribozyme K28 (128 nt) than in truncated RNAs (58 nt). Electrophoretic mobilities of self-thiophosphorylated products on organomercurial gels are distinct from the 5′ mono-thiophosphorylated product produced by reaction with polynucleotide kinase, potentially indicating simultaneous labeling of both sites within individual RNA strands. Our evidence supports a single, compact structure with local dynamics, rather than global rearrangement, as being responsible for dual-site phosphorylation.
Introduced to minimize open vial wastage, single-dose vaccine vials require more storage space and therefore may affect vaccine supply chains (i.e., the series of steps and processes entailed to deliver vaccines from manufacturers to patients). We developed a computational model of Thailand’s Trang province vaccine supply chain to analyze the effects of switching from a ten-dose measles vaccine presentation to each of the following: a single-dose Measles-Mumps-Rubella vaccine (which Thailand is currently considering) and a single-dose measles vaccine. While the Trang province vaccine supply chain would generally have enough storage and transport capacity to accommodate the switches, the added volume could push some locations’ storage and transport space utilization close to their limits. Single-dose vaccines would allow for more precise ordering and decrease open vial waste, but decrease reserves for unanticipated demand. Moreover, the added disposal and administration costs could far outweigh the costs saved from preventing open vial wastage.
Measles Vaccine; Vaccine Supply Chain; Single-Dose
We applied social network analyses to determine how hospitals within Orange County, California, are interconnected by patient sharing, a system which may have numerous public health implications.
Our analyses considered 2 general patient-sharing networks: uninterrupted patient sharing (UPS; i.e., direct interhospital transfers) and total patient sharing (TPS; i.e., all interhospital patient sharing, including patients with intervening nonhospital stays). We considered these networks at 3 thresholds of patient sharing: at least 1, at least 10, and at least 100 patients shared.
Geographically proximate hospitals were somewhat more likely to share patients, but many hospitals shared patients with distant hospitals. Number of patient admissions and percentage of cancer patients were associated with greater connectivity across the system. The TPS network revealed numerous connections not seen in the UPS network, meaning that direct transfers only accounted for a fraction of total patient sharing.
Our analysis demonstrated that Orange County’s 32 hospitals were highly and heterogeneously interconnected by patient sharing. Different hospital populations had different levels of influence over the patient-sharing network.
Influenza is a contagious respiratory disease responsible for annual seasonal epidemics in temperate climates. An understanding of how influenza spreads geographically and temporally within regions could result in improved public health prevention programs. The purpose of this study was to summarize the spatial and temporal spread of influenza using data obtained from the Pennsylvania Department of Health's influenza surveillance system.
Methodology and Findings
We evaluated the spatial and temporal patterns of laboratory-confirmed influenza cases in Pennsylvania, United States from six influenza seasons (2003–2009). Using a test of spatial autocorrelation, local clusters of elevated risk were identified in the South Central region of the state. Multivariable logistic regression indicated that lower monthly precipitation levels during the influenza season (OR = 0.52, 95% CI: 0.28, 0.94), fewer residents over age 64 (OR = 0.27, 95% CI: 0.10, 0.73) and fewer residents with more than a high school education (OR = 0.76, 95% CI: 0.61, 0.95) were significantly associated with membership in this cluster. In addition, time series analysis revealed a temporal lag in the peak timing of the influenza B epidemic compared to the influenza A epidemic.
These findings illustrate a distinct spatial cluster of cases in the South Central region of Pennsylvania. Further examination of the regional transmission dynamics within these clusters may be useful in planning public health influenza prevention programs.
Mathematical models can enhance our understanding of childhood infectious disease dynamics, but these models depend on appropriate parameter values that are often unknown and must be estimated from disease case data. In this paper, we develop a framework for efficient estimation of childhood infectious disease models with seasonal transmission parameters using continuous differential equations containing model and measurement noise. The problem is formulated using the simultaneous approach where all state variables are discretized, and the discretized differential equations are included as constraints, giving a large-scale algebraic nonlinear programming problem that is solved using a nonlinear primal–dual interior-point solver. The technique is demonstrated using measles case data from three different locations having different school holiday schedules, and our estimates of the seasonality of the transmission parameter show strong correlation to school term holidays. Our approach gives dramatic efficiency gains, showing a 40–400-fold reduction in solution time over other published methods. While our approach has an increased susceptibility to bias over techniques that integrate over the entire unknown state-space, a detailed simulation study shows no evidence of bias. Furthermore, the computational efficiency of our approach allows for investigation of a large model space compared with more computationally intensive approaches.
nonlinear optimization; measles; infectious diseases; mathematical programming; Gauss–Lobatto collocation