Uncertainty and sensitivity analysis of the basic reproduction number of diphtheria: a case study of a Rohingya refugee camp in Bangladesh, November-December 2017

Analysis of the impact of COVID-19 variants and vaccination on the time-varying reproduction number: statistical methods

Introduction

The COVID-19 pandemic has profoundly impacted global health systems, requiring the monitoring of infection waves and strategies to control transmission. Estimating the time-varying reproduction number is crucial for understanding the epidemic and guiding interventions.

Methods

Probability distributions of serial interval are estimated for Pre-Delta and Delta periods. We conducted a comparative analysis of time-varying reproduction numbers, taking into account population immunity and variant differences. We incorporated the regional heterogeneity and age distribution of the population, as well as the evolving variants and vaccination rates over time. COVID-19 transmission dynamics were analyzed with variants and vaccination.

Results

The reproduction number is computed with and without considering variant-based immunity. In addition, values of reproduction number significantly differed by variants, emphasizing immunity's importance. Enhanced vaccination efforts and stringent control measures were effective in reducing the transmission of the Delta variant. Conversely, Pre-Delta variant appeared less influenced by immunity levels, due to lower vaccination rates. Furthermore, during the Pre-Delta period, there was a significant difference between the region-specific and the non-region-specific reproduction numbers, with particularly distinct pattern differences observed in Gangwon, Gyeongbuk, and Jeju in Korea.

Discussion

This research elucidates the dynamics of COVID-19 transmission concerning the dominance of the Delta variant, the efficacy of vaccinations, and the influence of immunity levels. It highlights the necessity for targeted interventions and extensive vaccination coverage. This study makes a significant contribution to the understanding of disease transmission mechanisms and informs public health strategies.

Wastewater surveillance beyond COVID-19: a ranking system for communicable disease testing in the tri-county Detroit area, Michigan, USA

Introduction

Throughout the coronavirus disease 2019 (COVID-19) pandemic, wastewater surveillance has been utilized to monitor the disease in the United States through routine national, statewide, and regional monitoring projects. A significant canon of evidence was produced showing that wastewater surveillance is a credible and effective tool for disease monitoring. Hence, the application of wastewater surveillance can extend beyond monitoring SARS-CoV-2 to encompass a diverse range of emerging diseases. This article proposed a ranking system for prioritizing reportable communicable diseases (CDs) in the Tri-County Detroit Area (TCDA), Michigan, for future wastewater surveillance applications at the Great Lakes Water Authority's Water Reclamation Plant (GLWA's WRP).

Methods

The comprehensive CD wastewater surveillance ranking system (CDWSRank) was developed based on 6 binary and 6 quantitative parameters. The final ranking scores of CDs were computed by summing the multiplication products of weighting factors for each parameter, and then were sorted based on decreasing priority. Disease incidence data from 2014 to 2021 were collected for the TCDA. Disease incidence trends in the TCDA were endowed with higher weights, prioritizing the TCDA over the state of Michigan.

Results

Disparities in incidences of CDs were identified between the TCDA and state of Michigan, indicating epidemiological differences. Among 96 ranked CDs, some top ranked CDs did not present relatively high incidences but were prioritized, suggesting that such CDs require significant attention by wastewater surveillance practitioners, despite their relatively low incidences in the geographic area of interest. Appropriate wastewater sample concentration methods are summarized for the application of wastewater surveillance as per viral, bacterial, parasitic, and fungal pathogens.

Discussion

The CDWSRank system is one of the first of its kind to provide an empirical approach to prioritize CDs for wastewater surveillance, specifically in geographies served by centralized wastewater collection in the area of interest. The CDWSRank system provides a methodological tool and critical information that can help public health officials and policymakers allocate resources. It can be used to prioritize disease surveillance efforts and ensure that public health interventions are targeted at the most potentially urgent threats. The CDWSRank system can be easily adopted to geographical locations beyond the TCDA.

Multidrug-resistant toxigenic Corynebacterium diphtheriae sublineage 453 with two novel resistance genomic islands

Antimicrobial therapy is important for case management of diphtheria, but knowledge on the emergence of multidrug-resistance in Corynebacterium diphtheriae is scarce. We report on the genomic features of two multidrug-resistant toxigenic isolates sampled from wounds in France 3 years apart. Both isolates were resistant to spiramycin, clindamycin, tetracycline, kanamycin and trimethoprim-sulfamethoxazole. Genes ermX, cmx, aph(3')-Ib, aph(6)-Id, aph(3')-Ic, aadA1, dfrA15, sul1, cmlA, cmlR and tet(33) were clustered in two genomic islands, one consisting of two transposons and one integron, the other being flanked by two IS6100 insertion sequences. One isolate additionally presented mutations in gyrA and rpoB and was resistant to ciprofloxacin and rifampicin. Both isolates belonged to sublineage 453 (SL453), together with 25 isolates from 11 other countries (https://bigsdb.pasteur.fr/diphtheria/). SL453 is a cosmopolitan toxigenic sublineage of C. diphtheriae, a subset of which acquired multidrug resistance. Even though penicillin, amoxicillin and erythromycin, recommended as the first line in the treatment of diphtheria, remain active, surveillance of diphtheria should consider the risk of dissemination of multidrug-resistant strains and their genetic elements.

Interactions between the Re-Emerging Pathogen Corynebacterium diphtheriae and Host Cells

Corynebacterium diphtheriae, the etiological agent of diphtheria, is a re-emerging pathogen, responsible for several thousand deaths per year. In addition to diphtheria, systemic infections, often by non-toxigenic strains, are increasingly observed. This indicates that besides the well-studied and highly potent diphtheria toxin, various other virulence factors may influence the progression of the infection. This review focuses on the known components of C. diphtheriae responsible for adhesion, invasion, inflammation, and cell death, as well as on the cellular signaling pathways activated upon infection.

Global Stability Analysis and Parameter Estimation for a Diphtheria Model: A Case Study of an Epidemic in Rohingya Refugee Camp in Bangladesh

In this article, we have developed a deterministic Susceptible-Latent-Infectious-Recovered (SLIR) model for diphtheria outbreaks. Here, we have studied a case of the diphtheria outbreak in the Rohingya refugee camp in Bangladesh to trace the disease dynamics and find out the peak value of the infection. Both analytical and numerical investigations have been performed on the model to find several remarkable behaviors like the positive and bounded solution, basic reproductive ratio, and equilibria such as disease extinction equilibrium and disease persistence equilibrium which are characterized depending on the basic reproductive ratio and global stability of the model using Lyapunov function for both equilibria. Parameter estimation has been performed to determine the values of the parameter from the daily case data using numerical technique and determined the value of the basic reproductive number for the outbreak as ℛ 0 = 5.86.

Epidemiological, clinical, and public health response characteristics of a large outbreak of diphtheria among the Rohingya population in Cox's Bazar, Bangladesh, 2017 to 2019: A retrospective study

BACKGROUND

Unrest in Myanmar in August 2017 resulted in the movement of over 700,000 Rohingya refugees to overcrowded camps in Cox's Bazar, Bangladesh. A large outbreak of diphtheria subsequently began in this population.

METHODS AND FINDINGS

Data were collected during mass vaccination campaigns (MVCs), contact tracing activities, and from 9 Diphtheria Treatment Centers (DTCs) operated by national and international organizations. These data were used to describe the epidemiological and clinical features and the control measures to prevent transmission, during the first 2 years of the outbreak. Between November 10, 2017 and November 9, 2019, 7,064 cases were reported: 285 (4.0%) laboratory-confirmed, 3,610 (51.1%) probable, and 3,169 (44.9%) suspected cases. The crude attack rate was 51.5 cases per 10,000 person-years, and epidemic doubling time was 4.4 days (95% confidence interval [CI] 4.2-4.7) during the exponential growth phase. The median age was 10 years (range 0-85), and 3,126 (44.3%) were male. The typical symptoms were sore throat (93.5%), fever (86.0%), pseudomembrane (34.7%), and gross cervical lymphadenopathy (GCL; 30.6%). Diphtheria antitoxin (DAT) was administered to 1,062 (89.0%) out of 1,193 eligible patients, with adverse reactions following among 229 (21.6%). There were 45 deaths (case fatality ratio [CFR] 0.6%). Household contacts for 5,702 (80.7%) of 7,064 cases were successfully traced. A total of 41,452 contacts were identified, of whom 40,364 (97.4%) consented to begin chemoprophylaxis; adherence was 55.0% (N = 22,218) at 3-day follow-up. Unvaccinated household contacts were vaccinated with 3 doses (with 4-week interval), while a booster dose was administered if the primary vaccination schedule had been completed. The proportion of contacts vaccinated was 64.7% overall. Three MVC rounds were conducted, with administrative coverage varying between 88.5% and 110.4%. Pentavalent vaccine was administered to those aged 6 weeks to 6 years, while tetanus and diphtheria (Td) vaccine was administered to those aged 7 years and older. Lack of adequate diagnostic capacity to confirm cases was the main limitation, with a majority of cases unconfirmed and the proportion of true diphtheria cases unknown.

CONCLUSIONS

To our knowledge, this is the largest reported diphtheria outbreak in refugee settings. We observed that high population density, poor living conditions, and fast growth rate were associated with explosive expansion of the outbreak during the initial exponential growth phase. Three rounds of mass vaccinations targeting those aged 6 weeks to 14 years were associated with only modestly reduced transmission, and additional public health measures were necessary to end the outbreak. This outbreak has a long-lasting tail, with Rt oscillating at around 1 for an extended period. An adequate global DAT stockpile needs to be maintained. All populations must have access to health services and routine vaccination, and this access must be maintained during humanitarian crises.

A spatial queuing model for the location decision of emergency medical vehicles for pandemic outbreaks: the case of Za'atari refugee camp

Purpose

Refugee camps can be severely struck by pandemics, like potential COVID-19 outbreaks, due to high population densities and often only base-level medical infrastructure. Fast responding medical systems can help to avoid spikes in infections and death rates as they allow the prompt isolation and treatment of patients. At the same time, the normal demand for emergency medical services has to be dealt with as well. The overall goal of this study is the design of an emergency service system that is appropriate for both types of demand.

Design/methodology/approach

A spatial hypercube queuing model (HQM) is developed that uses queuing-theory methods to determine locations for emergency medical vehicles (also called servers). Therefore, a general optimization approach is applied, and subsequently, virus outbreaks at various locations of the study areas are simulated to analyze and evaluate the solution proposed. The derived performance metrics offer insights into the behavior of the proposed emergency service system during pandemic outbreaks. The Za'atari refugee camp in Jordan is used as a case study.

Findings

The derived locations of the emergency medical system (EMS) can handle all non-virus-related emergency demands. If additional demand due to virus outbreaks is considered, the system becomes largely congested. The HQM shows that the actual congestion is highly dependent on the overall amount of outbreaks and the corresponding case numbers per outbreak. Multiple outbreaks are much harder to handle even if their cumulative average case number is lower than for one singular outbreak. Additional servers can mitigate the described effects and lead to enhanced resilience in the case of virus outbreaks and better values in all considered performance metrics.

Research limitations/implications

Some parameters that were assumed for simplification purposes as well as the overall model should be verified in future studies with the relevant designers of EMSs in refugee camps. Moreover, from a practitioners perspective, the application of the model requires, at least some, training and knowledge in the overall field of optimization and queuing theory.

Practical implications

The model can be applied to different data sets, e.g. refugee camps or temporary shelters. The optimization model, as well as the subsequent simulation, can be used collectively or independently. It can support decision-makers in the general location decision as well as for the simulation of stress-tests, like virus outbreaks in the camp area.

Originality/value

The study addresses the research gap in an optimization-based design of emergency service systems for refugee camps. The queuing theory-based approach allows the calculation of precise (expected) performance metrics for both the optimization process and the subsequent analysis of the system. Applied to pandemic outbreaks, it allows for the simulation of the behavior of the system during stress-tests and adds a further tool for designing resilient emergency service systems.

Fatal respiratory diphtheria caused by β-lactam-resistant Corynebacterium diphtheriae

BACKGROUND

Diphtheria is a potentially fatal respiratory disease caused by toxigenic Corynebacterium diphtheriae. Although resistance to erythromycin has been recognised, β-lactam resistance in toxigenic diphtheria has not been described. Here, we report a case of fatal respiratory diphtheria caused by toxigenic C. diphtheriae resistant to penicillin and all other β-lactam antibiotics and describe a novel mechanism of inducible carbapenem resistance associated with the acquisition of a mobile resistance element.

METHODS

Long-read whole genome sequencing was performed using Pacific Biosciences SMRT sequencing to determine the genome sequence of C. diphtheriae BQ11 and mechanism of β-lactam resistance. To investigate phenotypic inducibility of meropenem resistance, short read sequencing was performed using an Illumina NextSeq500 sequencer on the strain with and without exposure to meropenem.

RESULTS

BQ11 demonstrated high-level resistance to penicillin (benzylpenicillin MIC ≥ 256 μg/ml), β-lactam/β-lactamase inhibitors and cephalosporins (amoxicillin/clavulanic acid MIC ≥ 256 μg/mL; ceftriaxone MIC ≥ 8 μg/L). Genomic analysis of BQ11 identified acquisition of a novel transposon carrying the penicillin binding protein Pbp2c, responsible for resistance to penicillin and cephalosporins. When strain BQ11 was exposed to meropenem, selective pressure drove amplification of the transposon in a tandem array and led to a corresponding change from a low level to high level meropenem resistant phenotype.

CONCLUSIONS

We have identified a novel mechanism of inducible antibiotic resistance whereby isolates that appear to be carbapenem susceptible on initial testing can develop in vivo resistance to carbapenems with repeated exposure. This phenomenon could have significant implications for treatment of C. diphtheriae infection and may lead to clinical failure.

Clinical and Epidemiological Aspects of Diphtheria: A Systematic Review and Pooled Analysis

BACKGROUND

Diphtheria, once a major cause of childhood morbidity and mortality, all but disappeared following introduction of diphtheria vaccine. Recent outbreaks highlight the risk diphtheria poses when civil unrest interrupts vaccination and healthcare access. Lack of interest over the last century resulted in knowledge gaps about diphtheria's epidemiology, transmission, and control.

METHODS

We conducted 9 distinct systematic reviews on PubMed and Scopus (March-May 2018). We pooled and analyzed extracted data to fill in these key knowledge gaps.

RESULTS

We identified 6934 articles, reviewed 781 full texts, and included 266. From this, we estimate that the median incubation period is 1.4 days. On average, untreated cases are colonized for 18.5 days (95% credible interval [CrI], 17.7-19.4 days), and 95% clear Corynebacterium diphtheriae within 48 days (95% CrI, 46-51 days). Asymptomatic carriers cause 76% (95% confidence interval, 59%-87%) fewer cases over the course of infection than symptomatic cases. The basic reproductive number is 1.7-4.3. Receipt of 3 doses of diphtheria toxoid vaccine is 87% (95% CrI, 68%-97%) effective against symptomatic disease and reduces transmission by 60% (95% CrI, 51%-68%). Vaccinated individuals can become colonized and transmit; consequently, vaccination alone can only interrupt transmission in 28% of outbreak settings, making isolation and antibiotics essential. While antibiotics reduce the duration of infection, they must be paired with diphtheria antitoxin to limit morbidity.

CONCLUSIONS

Appropriate tools to confront diphtheria exist; however, accurate understanding of the unique characteristics is crucial and lifesaving treatments must be made widely available. This comprehensive update provides clinical and public health guidance for diphtheria-specific preparedness and response.

Uncertainty and sensitivity analyses of extinction probabilities suggest that adult female mortality is the weakest link for populations of tsetse (Glossina spp)

Background

A relatively simple life history allows us to derive an expression for the extinction probability of populations of tsetse, vectors of African sleeping sickness. We present the uncertainty and sensitivity analysis of the extinction probability, to offer key insights into factors affecting the control or eradication of tsetse populations.

Methods

We represent tsetse population growth as a branching process, and derive closed form estimates of population extinction from that model. Statistical and mathematical techniques are used to analyse the uncertainties in estimating extinction probability, and the sensitivity of the extinction probability to changes in input parameters representing the natural life history and vital dynamics of tsetse populations.

Results

For fixed values of input parameters, the sensitivity of extinction probability depends on the baseline parameter values. Extinction probability is most sensitive to the probability that a female is inseminated by a fertile male when daily pupal mortality is low, whereas the extinction probability is most sensitive to daily mortality rate for adult females when daily pupal mortality, and extinction probabilities, are high. Global uncertainty and sensitivity analysis show that daily mortality rate for adult females has the highest impact on the extinction probability.

Conclusions

The high correlation between extinction probability and daily female adult mortality gives a strong argument that control techniques which increase daily female adult mortality may be the single most effective means of ensuring eradication of tsetse population.

Tsetse flies (Glossina spp.) are vectors of African trypanosomiasis, a deadly disease commonly called sleeping sickness in humans and nagana in livestock. The relatively simple life history of tsetse enabled us to model its population growth as a stochastic branching process. We derived a closed-form expression for the probability that a population of tsetse goes extinct, as a function of death, birth, development and insemination rates in female tsetse. We analyzed the sensitivity of the extinction probability to the different input parameters, in a bid to identify parameters with the highest impact on extinction probability. This information can, potentially, inform policy direction for tsetse control/elimination. In all the scenarios we considered for the global sensitivity analysis, the daily mortality rate for adult females had the greatest impact on the magnitude of extinction probability. Our findings suggest that the mortality rate in the adult females is the weakest link in tsetse life history, and this fact should be exploited in achieving tsetse population control, or even eradication.

Impact of mass vaccination campaigns on measles transmission during an outbreak in Guinea, 2017

OBJECTIVE

To estimate the time-dependent measles effective reproduction number (R_t) as an indicator of the impact of three outbreak response vaccination (ORV) campaigns on measles transmission during a nationwide outbreak in Guinea.

METHODS

R_t represents the average number of secondary cases generated by a single primary case in a partially immune population during a given time period. Measles R_t was estimated using daily incidence data for 3952 outbreak-associated measles cases in Guinea in 2017 for the time periods prior to, between, and following each of three ORV campaigns using a simple and extensible mathematical model.

RESULTS

R_t was estimated to be above the threshold value of 1 during the initial growth period of the outbreak until the first ORV campaign began on March 13 (R_t = 1.60, 95% CI: 1.55-1.67). It subsequently dropped below 1 and remained <1 through the end of the year (range: 0.71-0.91), although low levels of transmission persisted.

CONCLUSIONS

Reduction in R_t coincided with implementation of the ORV campaigns, indicating success of the campaigns at maintaining measles transmission intensity below epidemic growth levels. However, persistent measles transmission remains an issue in Guinea due to insufficient levels of herd immunity. Estimation of R_t should be further leveraged to help decision makers and field staff understand outbreak progress and the timing and type of vaccination efforts needed to halt transmission.

Diphtheria

Diphtheria is a potentially fatal infection mostly caused by toxigenic Corynebacterium diphtheriae strains and occasionally by toxigenic C. ulcerans and C. pseudotuberculosis strains. Diphtheria is generally an acute respiratory infection, characterized by the formation of a pseudomembrane in the throat, but cutaneous infections are possible. Systemic effects, such as myocarditis and neuropathy, which are associated with increased fatality risk, are due to diphtheria toxin, an exotoxin produced by the pathogen that inhibits protein synthesis and causes cell death. Clinical diagnosis is confirmed by the isolation and identification of the causative Corynebacterium spp., usually by bacterial culture followed by enzymatic and toxin detection tests. Diphtheria can be treated with the timely administration of diphtheria antitoxin and antimicrobial therapy. Although effective vaccines are available, this disease has the potential to re-emerge in countries where the recommended vaccination programmes are not sustained, and increasing proportions of adults are becoming susceptible to diphtheria. Thousands of diphtheria cases are still reported annually from several countries in Asia and Africa, along with many outbreaks. Changes in the epidemiology of diphtheria have been reported worldwide. The prevalence of toxigenic Corynebacterium spp. highlights the need for proper clinical and epidemiological investigations to quickly identify and treat affected individuals, along with public health measures to prevent and contain the spread of this disease.

Whole Genome Sequencing for Surveillance of Diphtheria in Low Incidence Settings

Corynebacterium diphtheriae (C. diphtheriae) is a relatively rare pathogen in most Western countries. While toxin producing strains can cause pharyngeal diphtheria with potentially fatal outcomes, the more common presentation is wound infections. The diphtheria toxin is encoded on a prophage and can also be carried by Corynebacterium ulcerans and Corynebacterium pseudotuberculosis. Currently, across Europe, infections are mainly diagnosed in travelers and refugees from regions where diphtheria is more endemic, patients from urban areas with poor hygiene, and intravenous drug users. About half of the cases are non-toxin producing isolates. Rapid identification of the bacterial pathogen and toxin production is a critical element of patient and outbreak management. Beside the immediate clinical management of the patient, public health agencies should be informed of toxigenic C. diphtheriae diagnoses as soon as possible. The collection of case-related epidemiological data from the patient is often challenging due to language barriers and social circumstances. However, information on patient contacts, vaccine status and travel/refugee route, where appropriate, is critical, and should be documented. In addition, isolates should be characterized using high resolution typing, in order to identify transmissions and outbreaks. In recent years, whole genome sequencing (WGS) has become the gold standard of high-resolution typing methods, allowing detailed investigations of pathogen transmissions. De-centralized sequencing strategies with redundancy in sequencing capacities, followed by data exchange may be a valuable future option, especially since WGS becomes more available and portable. In this context, the sharing of sequence data, using public available platforms, is essential. A close interaction between microbiology laboratories, treating physicians, refugee centers, social workers, and public health officials is a key element in successful management of suspected outbreaks. Analyzing bacterial isolates at reference centers may further help to provide more specialized microbiological techniques and to standardize information, but this is also more time consuming during an outbreak. Centralized communication strategies between public health agencies and laboratories helps considerably in establishing and coordinating effective surveillance and infection control. We review the current literature on high-resolution typing of C. diphtheriae and share our own experience with the coordination of a Swiss-German outbreak.

Real-time analysis of the diphtheria outbreak in forcibly displaced Myanmar nationals in Bangladesh

BACKGROUND

Between August and December 2017, more than 625,000 Rohingya from Myanmar fled into Bangladesh, settling in informal makeshift camps in Cox's Bazar district and joining 212,000 Rohingya already present. In early November, a diphtheria outbreak hit the camps, with 440 reported cases during the first month. A rise in cases during early December led to a collaboration between teams from Médecins sans Frontières-who were running a provisional diphtheria treatment centre-and the London School of Hygiene and Tropical Medicine with the goal to use transmission dynamic models to forecast the potential scale of the outbreak and the resulting resource needs.

METHODS

We first adjusted for delays between symptom onset and case presentation using the observed distribution of reporting delays from previously reported cases. We then fit a compartmental transmission model to the adjusted incidence stratified by age group and location. Model forecasts with a lead time of 2 weeks were issued on 12, 20, 26 and 30 December and communicated to decision-makers.

RESULTS

The first forecast estimated that the outbreak would peak on 19 December in Balukhali camp with 303 (95% posterior predictive interval 122-599) cases and would continue to grow in Kutupalong camp, requiring a bed capacity of 316 (95% posterior predictive interval (PPI) 197-499). On 19 December, a total of 54 cases were reported, lower than forecasted. Subsequent forecasts were more accurate: on 20 December, we predicted a total of 912 cases (95% PPI 367-2183) and 136 (95% PPI 55-327) hospitalizations until the end of the year, with 616 cases actually reported during this period.

CONCLUSIONS

Real-time modelling enabled feedback of key information about the potential scale of the epidemic, resource needs and mechanisms of transmission to decision-makers at a time when this information was largely unknown. By 20 December, the model generated reliable forecasts and helped support decision-making on operational aspects of the outbreak response, such as hospital bed and staff needs, and with advocacy for control measures. Although modelling is only one component of the evidence base for decision-making in outbreak situations, suitable analysis and forecasting techniques can be used to gain insights into an ongoing outbreak.

Estimating the incidence and diagnosed proportion of HIV infections in Japan: a statistical modeling study

Background

Epidemiological surveillance of HIV infection in Japan involves two technical problems for directly applying a classical backcalculation method, i.e., (i) all AIDS cases are not counted over time and (ii) people diagnosed with HIV have received antiretroviral therapy, extending the incubation period. The present study aimed to address these issues and estimate the HIV incidence and the proportion of diagnosed HIV infections, using a simple statistical model.

Methods

From among Japanese nationals, yearly incidence data of HIV diagnoses and patients with AIDS who had not previously been diagnosed as HIV positive, from 1985 to 2017, were analyzed. Using the McKendrick partial differential equation, general convolution-like equations were derived, allowing estimation of the HIV incidence and the time-dependent rate of diagnosis. A likelihood-based approach was used to obtain parameter estimates.

Results

Assuming that the median incubation period was 10.0 years, the cumulative number of HIV infections was estimated to be 29,613 (95% confidence interval (CI): 29,059, 30,167) by the end of 2017, and the proportion of diagnosed HIV infections was estimated at 80.3% (95% CI [78.7%–82.0%]). Allowing the median incubation period to range from 7.5 to 12.3 years, the estimate of the proportion diagnosed can vary from 77% to 84%.

Discussion

The proportion of diagnosed HIV infections appears to have not yet reached 90% among Japanese nationals. Compared with the peak incidence from 2005–2008, new HIV infections have clearly been in a declining trend; however, there are still more than 1,000 new HIV infections per year in Japan. To increase the diagnosed proportion of HIV infections, it is critical to identify people who have difficulty accessing consultation, testing, and care, and to explore heterogeneous patterns of infection.

Modeling the elevated risk of yellow fever among travelers visiting Brazil, 2018

BACKGROUND

Unlike the epidemic of yellow fever from 2016 to 17 in Brazil mostly restricted to the States of Minas Gerais and Espirito Santo, the epidemic from 2017 to 18 mainly involved São Paulo and Rio de Janeiro and resulted in multiple international disseminations. To understand mechanisms behind this observation, the present study analyzed the distribution of imported cases from Brazil, 2018.

METHODS

A statistical model was employed to capture the risk of importing yellow fever by returning international travelers from Brazil. We estimated the relative risk of importation among travelers by the extent of wealth measured by GDP per capita and the relative risk obtained by random assignment of travelers' destination within Brazil by the relative population size.

RESULTS

Upper-half wealthier countries had 2.1 to 3.4 times greater risk of importation than remainders. Even among countries with lower half of GDP per capita, the risk of importation was 2.5 to 2.8 times greater than assuming that the risk of travelers' infection within Brazil is determined by the regional population size.

CONCLUSIONS

Travelers from wealthier countries were at elevated risk of yellow fever, allowing us to speculate that travelers' local destination and behavior at high risk of infection are likely to act as a key determinant of the heterogeneous risk of importation. It is advised to inform travelers over the ongoing geographic foci of transmission, and if it appears unavoidable to visit tourist destination that has the history of producing imported cases, travelers must be strongly advised to receive vaccination in advance.