Use of Approximate Bayesian Computation to Assess and Fit Models of Mycobacterium leprae to Predict Outcomes of the Brazilian Control Program

Hansen’s disease (leprosy) elimination has proven difficult in several countries, including Brazil, and there is a need for a mathematical model that can predict control program efficacy. This study applied the Approximate Bayesian Computation algorithm to fit 6 different proposed models to each of the 5 regions of Brazil, then fitted hierarchical models based on the best-fit regional models to the entire country. The best model proposed for most regions was a simple model. Posterior checks found that the model results were more similar to the observed incidence after fitting than before, and that parameters varied slightly by region. Current control programs were predicted to require additional measures to eliminate Hansen’s Disease as a public health problem in Brazil.     

Spatial Analysis Spotlighting Early Childhood Leprosy Transmission in a Hyperendemic Municipality of the Brazilian Amazon Region

Background

More than 200,000 new cases of leprosy were reported by 105 countries in 2011. The disease is a public health problem in Brazil, particularly within high-burden pockets in the Amazon region where leprosy is hyperendemic among children.

Methodology

We applied geographic information systems and spatial analysis to determine the spatio-temporal pattern of leprosy cases in a hyperendemic municipality of the Brazilian Amazon region (Castanhal). Moreover, we performed active surveillance to collect clinical, epidemiological and serological data of the household contacts of people affected by leprosy and school children in the general population. The occurrence of subclinical infection and overt disease among the evaluated individuals was correlated with the spatio-temporal pattern of leprosy.

Principal Findings

The pattern of leprosy cases showed significant spatio-temporal heterogeneity (p<0.01). Considering 499 mapped cases, we found spatial clusters of high and low detection rates and spatial autocorrelation of individual cases at fine spatio-temporal scales. The relative risk of contracting leprosy in one specific cluster with a high detection rate is almost four times the risk in the areas of low detection rate (RR = 3.86; 95% CI = 2.26–6.59; p<0.0001). Eight new cases were detected among 302 evaluated household contacts: two living in areas of clusters of high detection rate and six in hyperendemic census tracts. Of 188 examined students, 134 (71.3%) lived in hyperendemic areas, 120 (63.8%) were dwelling less than 100 meters of at least one reported leprosy case, 125 (66.5%) showed immunological evidence (positive anti-PGL-I IgM titer) of subclinical infection, and 9 (4.8%) were diagnosed with leprosy (8 within 200 meters of a case living in the same area).

Conclusions/Significance

Spatial analysis provided a better understanding of the high rate of early childhood leprosy transmission in this region. These findings can be applied to guide leprosy control programs to target intervention to high risk areas.     

Patterns of Migration and Risks Associated with Leprosy among Migrants in Maranh?o,Brazil

Leprosy remains a public health problem in Brazil with new case incidence exceeding World Health Organization (WHO) goals in endemic clusters throughout the country. Migration can facilitate movement of disease between endemic and non-endemic areas, and has been considered a possible factor in continued leprosy incidence in Brazil. A study was conducted to investigate migration as a risk factor for leprosy. The study had three aims: (1) examine past five year migration as a risk factor for leprosy, (2) describe and compare geographic and temporal patterns of migration among past 5-year migrants with leprosy and a control group, and (3) examine social determinants of health associated with leprosy among past 5-year migrants. The study implemented a matched case-control design and analysis comparing individuals newly diagnosed with leprosy (n = 340) and a clinically unapparent control group (n = 340) without clinical signs of leprosy, matched for age, sex and location in four endemic municipalities in the state of Maranhão, northeastern Brazil. Fishers exact test was used to conduct bivariate analyses. A multivariate logistic regression analysis was employed to control for possible confounding variables. Eighty cases (23.5%) migrated 5-years prior to diagnosis, and 55 controls (16.2%) migrated 5-years prior to the corresponding case diagnosis. Past 5 year migration was found to be associated with leprosy (OR: 1.59; 95% CI 1.07–2.38; p = 0.02), and remained significantly associated with leprosy after controlling for leprosy contact in the family, household, and family/household contact. Poverty, as well as leprosy contact in the family, household and other leprosy contact, was associated with leprosy among past 5-year migrants in the bivariate analysis. Alcohol consumption was also associated with leprosy, a relevant risk factor in susceptibility to infection that should be explored in future research. Our findings provide insight into patterns of migration to localize focused control efforts in endemic areas with high population mobility.     

The state of the leprosy epidemic in Yunnan,China 2011–2020: A spatial and spatiotemporal analysis,highlighting areas for intervention

BackgroundDespite public health efforts to reduce the leprosy burden in Yunnan, China, leprosy remains an important public health problem in some specific areas. We analyzed the epidemiological characteristics and spatial distribution of leprosy in Yunnan, China, and provide data to guide disease prevention and control efforts.Methodology/principal findingsThe surveillance data of newly detected leprosy cases in Yunnan, China, during 2011–2020 were extracted from the LEPROSY MANAGEMANT INFORMATION SYSTEM IN CHINA (LEPMIS), and spatial distribution analysis, spatial autocorrelation analysis, and spatiotemporal scanning were performed with ArcGIS 10.6.1, GeoDa 1.8.8, and SaTScan 9.4.3 software, respectively. A total of 1907 newly detected leprosy cases were reported in Yunnan, China, during 2011–2020. The new case detection rate (NCDR) decreased from 0.62 in 2011 to 0.25 in 2020, with an annual incidence of 0.41/100,000 population. The proportions of multibacillary (MB) cases, cases in female patients, cases causing grade 2 physical disability (G2D), and cases in pediatric patients were 67.07%, 33.93%, 17.99%, and 2.83%, respectively. The number of counties with an incidence above 1/100,000 population decreased from 30 in 2011 to 8 in 2020. The Moran’s I of leprosy in Yunnan, China, during 2011–2020 ranged from 0.076 to 0.260, indicating the presence of spatial clusters. Local spatial autocorrelation (LSA) analysis showed that high-high cluster areas (hot spots) were mainly distributed in the southeastern, northern, and northwestern regions. Spatiotemporal scanning showed three clusters with high NCDRs. The probably primary clusters, occurring during January 1, 2011–December 31, 2015, covered 11 counties in the southeastern region (RR = 5.046515, LRR = 271.749664, P = 0.000).ConclusionThe number of leprosy cases in Yunnan decreased overall, although some high-NCDR regions remained. Geographic information system (GIS) analysis coupled with spatial analysis indicated regions with leprosy clusters. Continuous leprosy prevention and control strategies in Yunnan Province should be established, and interventions in high-risk regions should be prioritized and further strengthened.     

Leprosy New Case Detection Trends and the Future Effect of Preventive Interventions in Pará State,Brazil: A Modelling Study

BackgroundLeprosy remains a public health problem in Brazil. Although the overall number of new cases is declining, there are still areas with a high disease burden, such as Pará State in the north of the country. We aim to predict future trends in new case detection rate (NCDR) and explore the potential impact of contact tracing and chemoprophylaxis on NCDR in Pará State.MethodsWe used SIMCOLEP, an existing individual-based model for the transmission and control of M. leprae, in a population structured by households. The model was quantified to simulate the population and observed NCDR of leprosy in Pará State for the period 1990 to 2014. The baseline scenario was the current control program, consisting of multidrug therapy, passive case detection, and active case detection from 2003 onwards. Future projections of the NCDR were made until 2050 given the continuation of the current control program (i.e. baseline). We further investigated the potential impact of two scenarios for future control of leprosy: 1) discontinuation of contact tracing; and 2) continuation of current control in combination with chemoprophylaxis. Both scenarios started in 2015 and were projected until 2050.ResultsThe modelled NCDR in Pará State after 2014 shows a continuous downward trend, reaching the official elimination target of 10 cases per 100,000 population by 2030. The cessation of systematic contact tracing would not result in a higher NCDR in the long run. Systematic contact tracing in combination with chemoprophylaxis for contacts would reduce the NCDR by 40% and bring attainment of the elimination target two years forward to 2028.ConclusionThe NCDR of leprosy continues to decrease in Pará State. Elimination of leprosy as a public health problem could possibly be achieved around 2030, if the current control program is maintained. Providing chemoprophylaxis would decrease the NCDR further and would bring elimination forward by two years.     

Effect of the Brazilian Conditional Cash Transfer and Primary Health Care Programs on the New Case Detection Rate of Leprosy

Background

Social determinants can affect the transmission of leprosy and its progression to disease. Not much is known about the effectiveness of welfare and primary health care policies on the reduction of leprosy occurrence. The aim of this study is to evaluate the impact of the Brazilian cash transfer (Bolsa Família Program-BFP) and primary health care (Family Health Program-FHP) programs on new case detection rate of leprosy.

Methodology/Principal Findings

We conducted the study with a mixed ecological design, a combination of an ecological multiple-group and time-trend design in the period 2004–2011 with the Brazilian municipalities as unit of analysis. The main independent variables were the BFP and FHP coverage at the municipal level and the outcome was new case detection rate of leprosy. Leprosy new cases, BFP and FHP coverage, population and other relevant socio-demographic covariates were obtained from national databases. We used fixed-effects negative binomial models for panel data adjusted for relevant socio-demographic covariates. A total of 1,358 municipalities were included in the analysis. In the studied period, while the municipal coverage of BFP and FHP increased, the new case detection rate of leprosy decreased. Leprosy new case detection rate was significantly reduced in municipalities with consolidated BFP coverage (Risk Ratio 0.79; 95% CI  = 0.74–0.83) and significantly increased in municipalities with FHP coverage in the medium (72–95%) (Risk Ratio 1.05; 95% CI  = 1.02–1.09) and higher coverage tertiles (>95%) (Risk Ratio 1.12; 95% CI  = 1.08–1.17).

Conclusions

At the same time the Family Health Program had been effective in increasing the new case detection rate of leprosy in Brazil, the Bolsa Família Program was associated with a reduction of the new case detection rate of leprosy that we propose reflects a reduction in leprosy incidence.     

A Retrospective Study of the Epidemiology of Leprosy in Cebu: An Eleven-Year Profile

Background

Cebu has been one of the most leprosy endemic areas in the Philippines. Despite the high coverage rates of multiple drug therapy (MDT) and high BCG-vaccine coverage in children, leprosy control authorities believe that leprosy transmission and incidence (as evidence by continuing new case detection in both adults and children) have not declined as expected, once leprosy had been eliminated.In response to the concerns communicated by the authorities regarding ongoing leprosy transmission in Cebu, this study aims to examine the evidence for the hypothesized ongoing transmission, both in children and adults. Furthermore, it will be assessed which groups and areas are experiencing a continuing risk of leprosy infection; this can form a starting point for more targeted approaches to leprosy control.

Methodology & Principal Findings

Case records from 2000–2010 were retrospectively collected from the Leonard Wood Memorial Clinic archives, and all other clinics on the island where leprosy was treated. Between 2000 and 2010, 3288 leprosy cases were detected. The overall five year case notification rate (CNR) dropped significantly from 47.35 (2001–2005) to 29.21 cases (2006–2010) per 100.000 population. Smaller CNRs were reported for children; however the decline in child-CNR over the same period was minimal. Furthermore, no increase in median age of notification in children or adults was found between 2000 and 2010. Population-adjusted clustering of leprosy cases was mainly detected in urban and peri-urban areas.

Conclusions & Significance

Although the overall CNR declined significantly, CNR seems to be rather static in lower risk populations and areas. Cases are mainly found in urban areas, however CNRs in these areas decline at a much faster rate than in the lower endemic rural areas. A similar situation was found when comparing adults and children: CNRs observed in children were lower than in adults, but further decline (and elimination) of these childhood CNRs was found to be difficult. Moreover, the median age of notification in children has remained stable, suggesting transmission is still on-going.It is unclear why many years of good MDT-coverage and a gradual decline in CNR have not been accompanied by evidence of reduced transmission, especially beyond a certain threshold level of case notification. We believe that a new approach to leprosy control is required to tackle transmission more directly. The most promising approach may involve chemoprophylaxis and/or immunoprophylaxis interventions, targeted at high risk (urban) areas and groups such as household contacts, followed by a different approach once decline in CNR starts to level off. Identified clusters and trends can form the starting point for implementing this approach.     

A proposed framework for the development and qualitative evaluation of West Nile virus models and their application to local public health decision-making

West Nile virus (WNV) is a globally distributed mosquito-borne virus of great public health concern. The number of WNV human cases and mosquito infection patterns vary in space and time. Many statistical models have been developed to understand and predict WNV geographic and temporal dynamics. However, these modeling efforts have been disjointed with little model comparison and inconsistent validation. In this paper, we describe a framework to unify and standardize WNV modeling efforts nationwide. WNV risk, detection, or warning models for this review were solicited from active research groups working in different regions of the United States. A total of 13 models were selected and described. The spatial and temporal scales of each model were compared to guide the timing and the locations for mosquito and virus surveillance, to support mosquito vector control decisions, and to assist in conducting public health outreach campaigns at multiple scales of decision-making. Our overarching goal is to bridge the existing gap between model development, which is usually conducted as an academic exercise, and practical model applications, which occur at state, tribal, local, or territorial public health and mosquito control agency levels. The proposed model assessment and comparison framework helps clarify the value of individual models for decision-making and identifies the appropriate temporal and spatial scope of each model. This qualitative evaluation clearly identifies gaps in linking models to applied decisions and sets the stage for a quantitative comparison of models. Specifically, whereas many coarse-grained models (county resolution or greater) have been developed, the greatest need is for fine-grained, short-term planning models (m–km, days–weeks) that remain scarce. We further recommend quantifying the value of information for each decision to identify decisions that would benefit most from model input.     

Low risk of relapse and deformity among leprosy patients who completed multi-drug therapy regimen from 2005 to 2010: A cohort study from four districts in South India

IntroductionRelapse of leprosy among patients released from treatment (RFT) is an indicator of the success of anti-leprosy treatment. Due to inadequate follow-up, relapse in leprosy patients after RFT is not systematically documented in India. Relapsed leprosy patients pose a risk in the transmission of leprosy bacilli. We determined the incidence of relapse and deformity among the patients RFT from the leprosy control programme in four districts in South India.MethodsWe conducted two follow-up surveys in 2012 and 2014 among the leprosy patients RFT between 2005 and 2010. We assessed them for any symptoms or signs of relapse, persistence and deformity. We collected slit skin samples (SSS) for smear examination. We calculated overall incidence of relapse and deformity per 1000 person-years (PY) with 95% confidence intervals (CI) and cumulative risk of relapse.ResultsOverall, we identified 69 relapse events, 58 and 11, during the first and second follow-up surveys, respectively. The incidence of relapse was 5.42 per 1000 PY, which declined over the years after RFT. The cumulative risk of relapse was 2.24%. The rate of deformity among the relapsed patients was 30.9%. The overall incidence of deformity was 1.65 per 1000 person years. The duration of M. leprae detection in smears ranged between 2.38 and 7.67 years.ConclusionsLow relapse and deformity rates in leprosy RFT patients are indicative of treatment effectiveness. However, a higher proportion of detection of deformity among relapsed cases is a cause for concern. Periodic follow-up of RFT patients for up to 3 years to detect relapses early and ensure appropriate treatment will minimize the development of deformity among relapsed patients.     

Estimating underreporting of leprosy in Brazil using a Bayesian approach

BackgroundLeprosy remains concentrated among the poorest communities in low-and middle-income countries and it is one of the primary infectious causes of disability. Although there have been increasing advances in leprosy surveillance worldwide, leprosy underreporting is still common and can hinder decision-making regarding the distribution of financial and health resources and thereby limit the effectiveness of interventions. In this study, we estimated the proportion of unreported cases of leprosy in Brazilian microregions.Methodology/Principal findingsUsing data collected between 2007 to 2015 from each of the 557 Brazilian microregions, we applied a Bayesian hierarchical model that used the presence of grade 2 leprosy-related physical disabilities as a direct indicator of delayed diagnosis and a proxy for the effectiveness of local leprosy surveillance program. We also analyzed some relevant factors that influence spatial variability in the observed mean incidence rate in the Brazilian microregions, highlighting the importance of socioeconomic factors and how they affect the levels of underreporting. We corrected leprosy incidence rates for each Brazilian microregion and estimated that, on average, 33,252 (9.6%) new leprosy cases went unreported in the country between 2007 to 2015, with this proportion varying from 8.4% to 14.1% across the Brazilian States.Conclusions/SignificanceThe magnitude and distribution of leprosy underreporting were adequately explained by a model using Grade 2 disability as a marker for the ability of the system to detect new missing cases. The percentage of missed cases was significant, and efforts are warranted to improve leprosy case detection. Our estimates in Brazilian microregions can be used to guide effective interventions, efficient resource allocation, and target actions to mitigate transmission.     

HIV-1 Superinfection Occurs Less Frequently Than Initial Infection in a Cohort of High-Risk Kenyan Women

HIV superinfection (reinfection) has been reported in several settings, but no study has been designed and powered to rigorously compare its incidence to that of initial infection. Determining whether HIV infection reduces the risk of superinfection is critical to understanding whether an immune response to natural HIV infection is protective. This study compares the incidence of initial infection and superinfection in a prospective seroincident cohort of high-risk women in Mombasa, Kenya. A next-generation sequencing-based pipeline was developed to screen 129 women for superinfection. Longitudinal plasma samples at <6 months, >2 years and one intervening time after initial HIV infection were analyzed. Amplicons in three genome regions were sequenced and a median of 901 sequences obtained per gene per timepoint. Phylogenetic evidence of polyphyly, confirmed by pairwise distance analysis, defined superinfection. Superinfection timing was determined by sequencing virus from intervening timepoints. These data were combined with published data from 17 additional women in the same cohort, totaling 146 women screened. Twenty-one cases of superinfection were identified for an estimated incidence rate of 2.61 per 100 person-years (pys). The incidence rate of initial infection among 1910 women in the same cohort was 5.75 per 100pys. Andersen-Gill proportional hazards models were used to compare incidences, adjusting for covariates known to influence HIV susceptibility in this cohort. Superinfection incidence was significantly lower than initial infection incidence, with a hazard ratio of 0.47 (CI 0.29–0.75, p = 0.0019). This lower incidence of superinfection was only observed >6 months after initial infection. This is the first adequately powered study to report that HIV infection reduces the risk of reinfection, raising the possibility that immune responses to natural infection are partially protective. The observation that superinfection risk changes with time implies a window of protection that coincides with the maturation of HIV-specific immunity.     

A Data-Driven Mathematical Model of CA-MRSA Transmission among Age Groups: Evaluating the Effect of Control Interventions

Community associated methicillin-resistant Staphylococcus aureus (CA-MRSA) has become a major cause of skin and soft tissue infections (SSTIs) in the US. We developed an age-structured compartmental model to study the spread of CA-MRSA at the population level and assess the effect of control intervention strategies. We used Monte-Carlo Markov Chain (MCMC) techniques to parameterize our model using monthly time series data on SSTIs incidence in children (≤19 years) during January 2004 -December 2006 in Maricopa County, Arizona. Our model-based forecast for the period January 2007–December 2008 also provided a good fit to data. We also carried out an uncertainty and sensitivity analysis on the control reproduction number, which we estimated at 1.3 (95% CI [1.2,1.4]) based on the model fit to data. Using our calibrated model, we evaluated the effect of typical intervention strategies namely reducing the contact rate of infected individuals owing to awareness of infection and decolonization strategies targeting symptomatic infected individuals on both and the long-term disease dynamics. We also evaluated the impact of hypothetical decolonization strategies targeting asymptomatic colonized individuals. We found that strategies focused on infected individuals were not capable of achieving disease control when implemented alone or in combination. In contrast, our results suggest that decolonization strategies targeting the pediatric population colonized with CA-MRSA have the potential of achieving disease elimination.     

Survey to identify Mycobacterium leprae-infected household contacts of patients from prevalent regions of leprosy in Colombia

Leprosy in Colombia is in the post-elimination phase; nevertheless, there are regions of this country where the incidence is still around 3-4/100,000. Early detection of leprosy patients is a priority for achieving control and elimination of leprosy; however, the clinical exam is not very sensitive and thus, the majority of patients are diagnosed only when they demonstrate lesions, and damage to the nerves and skin has already occurred. The goal of the present study was to identify Mycobacterium leprae infection and immune responses in household contacts (HHC) of leprosy patients from three prevalent regions of Colombia. Clinical examination, the Mitsuda test, evaluation of IgM anti-PGL-I in the serum, the bacillar index (BI), and polymerase chain reaction (PCR) from nasal swabs (NS) were performed for 402 HHC of 104 leprosy patients during a cross-sectional survey. Positive titers for IgM anti-PGL1 were found for 54 HHC, and PCR-positive NS for 22. The Mitsuda reaction was negative for 38 HHC, although three were positive for IgM anti-PGL-1 titers. The data document that leprosy transmission among HHC is still occurring in a non-endemic country.     

TAIMA (Stop) TB: The Impact of a Multifaceted TB Awareness and Door-to-Door Campaign in Residential Areas of High Risk for TB in Iqaluit,Nunavut

Background

The incidence rate of active tuberculosis (TB) disease in the Canadian Territory of Nunavut has shown a rising trend over the past 10 years. In 2010 it was 60 times greater than the national incidence rate. The objective of the Taima (translates to “stop” in Inuktitut) TB study was to implement and evaluate a public health campaign to enhance existing TB prevention efforts in Nunavut.

Methods

A TB awareness campaign followed by a door-to-door screening campaign was carried out in Iqaluit, Nunavut. The aim of the campaign was to raise awareness about TB, and to provide in-home screening and treatment for people living in residential areas at high risk for TB. Screening was based on geographic location rather than on individual risk factors.

Results

During the general awareness campaign an increase in the number of people who requested TB testing at the local public health clinic was observed. However, this increase was not sustained following cessation of the awareness campaign. Targeted TB screening in high risk residential areas in Iqaluit resulted in 224 individuals having TSTs read, and detection of 42 previously unidentified cases of latent TB, (overall yield of 18.8% or number needed to screen = 5.3). These cases of latent TB infection (LTBI) were extra cases that had not been picked up by traditional screening practices (34% relative increase within the community). This resulted in a 33% relative increase in the completion of LTBI treatment within the community. The program directly and indirectly identified 5/17 new cases of active TB disease in Iqaluit during the study period (29.5% of all incident cases).

Conclusions

While contact tracing investigations remain a cornerstone of TB prevention, additional awareness, screening, and treatment programs like Taima TB may contribute to the successful control of TB in Aboriginal communities.     

Bayesian evidence synthesis for a transmission dynamic model for HIV among men who have sex with men

Understanding infectious disease dynamics and the effect on prevalence and incidence is crucial for public health policies. Disease incidence and prevalence are typically not observed directly and increasingly are estimated through the synthesis of indirect information from multiple data sources. We demonstrate how an evidence synthesis approach to the estimation of human immunodeficiency virus (HIV) prevalence in England and Wales can be extended to infer the underlying HIV incidence. Diverse time series of data can be used to obtain yearly "snapshots" (with associated uncertainty) of the proportion of the population in 4 compartments: not at risk, susceptible, HIV positive but undiagnosed, and diagnosed HIV positive. A multistate model for the infection and diagnosis processes is then formulated by expressing the changes in these proportions by a system of differential equations. By parameterizing incidence in terms of prevalence and contact rates, HIV transmission is further modeled. Use of additional data or prior information on demographics, risk behavior change and contact parameters allows simultaneous estimation of the transition rates, compartment prevalences, contact rates, and transmission probabilities.     

Major acute cardiovascular events after dengue infection–A population-based observational study

BackgroundDengue virus (DENV) infection may be associated with increased risks of major adverse cardiovascular effect (MACE), but a large-scale study evaluating the association between DENV infection and MACEs is still lacking.Methods and findingsAll laboratory confirmed dengue cases in Taiwan during 2009 and 2015 were included by CDC notifiable database. The self-controlled case-series design was used to evaluate the association between DENV infection and MACE (including acute myocardial infarction [AMI], heart failure and stroke). The "risk interval" was defined as the first 7 days after the diagnosis of DENV infection and the "control interval" as 1 year before and 1 year after the risk interval. The incidence rate ratio (IRR) and 95% confidence interval (CI) for MACE were estimated by conditional Poisson regression. Finally, the primary outcome of the incidence of MACEs within one year of dengue was observed in 1,247 patients. The IRR of MACEs was 17.9 (95% CI 15.80–20.37) during the first week after the onset of DENV infection observed from 1,244 eligible patients. IRR were significantly higher for hemorrhagic stroke (10.9, 95% CI 6.80–17.49), ischemic stroke (15.56, 95% CI 12.44–19.47), AMI (13.53, 95% CI 10.13–18.06), and heart failure (27.24, 95% CI 22.67–32.73). No increased IRR was observed after day 14.ConclusionsThe risks for MACEs are significantly higher in the immediate time period after dengue infection. Since dengue infection is potentially preventable by early recognition and vaccination, the dengue-associated MACE should be taken into consideration when making public health management policies.     

Epidemiologic data and pathogen genome sequences: a powerful synergy for public health

Epidemiologists aim to inform the design of public health interventions with evidence on the evolution, emergence and spread of infectious diseases. Sequencing of pathogen genomes, together with date, location, clinical manifestation and other relevant data about sample origins, can contribute to describing nearly every aspect of transmission dynamics, including local transmission and global spread. The analyses of these data have implications for all levels of clinical and public health practice, from institutional infection control to policies for surveillance, prevention and treatment. This review highlights the range of epidemiological questions that can be addressed from the combination of genome sequence and traditional ‘line lists’ (tables of epidemiological data where each line includes demographic and clinical features of infected individuals). We identify opportunities for these data to inform interventions that reduce disease incidence and prevalence. By considering current limitations of, and challenges to, interpreting these data, we aim to outline a research agenda to accelerate the genomics-driven transformation in public health microbiology.