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Streptococcus pneumoniae is a leading cause of pneumonia and meningitis worldwide. Many different serotypes co-circulate endemically in any one location1,2. The extent and mechanisms of spread and vaccine-driven changes in fitness and antimicrobial resistance remain largely unquantified. Here using geolocated genome sequences from South Africa (n = 6,910, collected from 2000 to 2014), we developed models to reconstruct spread, pairing detailed human mobility data and genomic data. Separately, we estimated the population-level changes in fitness of strains that are included (vaccine type (VT)) and not included (non-vaccine type (NVT)) in pneumococcal conjugate vaccines, first implemented in South Africa in 2009. Differences in strain fitness between those that are and are not resistant to penicillin were also evaluated. We found that pneumococci only become homogenously mixed across South Africa after 50 years of transmission, with the slow spread driven by the focal nature of human mobility. Furthermore, in the years following vaccine implementation, the relative fitness of NVT compared with VT strains increased (relative risk of 1.68; 95% confidence interval of 1.59-1.77), with an increasing proportion of these NVT strains becoming resistant to penicillin. Our findings point to highly entrenched, slow transmission and indicate that initial vaccine-linked decreases in antimicrobial resistance may be transient.
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Aptidão Genética , Mapeamento Geográfico , Streptococcus pneumoniae , Humanos , Aptidão Genética/efeitos dos fármacos , Aptidão Genética/genética , Genoma Bacteriano/genética , Resistência às Penicilinas/efeitos dos fármacos , Resistência às Penicilinas/genética , Penicilinas/farmacologia , Infecções Pneumocócicas/epidemiologia , Infecções Pneumocócicas/imunologia , Infecções Pneumocócicas/microbiologia , Infecções Pneumocócicas/transmissão , Vacinas Pneumocócicas/imunologia , Sorogrupo , África do Sul/epidemiologia , Streptococcus pneumoniae/efeitos dos fármacos , Streptococcus pneumoniae/genética , Streptococcus pneumoniae/imunologia , Streptococcus pneumoniae/isolamento & purificação , Vacinas Conjugadas/imunologia , Vacina Pneumocócica Conjugada Heptavalente/imunologia , LocomoçãoRESUMO
Estimating the size of the coronavirus disease 2019 (COVID-19) pandemic and the infection severity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is made challenging by inconsistencies in the available data. The number of deaths associated with COVID-19 is often used as a key indicator for the size of the epidemic, but the observed number of deaths represents only a minority of all infections1,2. In addition, the heterogeneous burdens in nursing homes and the variable reporting of deaths of older individuals can hinder direct comparisons of mortality rates and the underlying levels of transmission across countries3. Here we use age-specific COVID-19-associated death data from 45 countries and the results of 22 seroprevalence studies to investigate the consistency of infection and fatality patterns across multiple countries. We find that the age distribution of deaths in younger age groups (less than 65 years of age) is very consistent across different settings and demonstrate how these data can provide robust estimates of the share of the population that has been infected. We estimate that the infection fatality ratio is lowest among 5-9-year-old children, with a log-linear increase by age among individuals older than 30 years. Population age structures and heterogeneous burdens in nursing homes explain some but not all of the heterogeneity between countries in infection fatality ratios. Among the 45 countries included in our analysis, we estimate that approximately 5% of these populations had been infected by 1 September 2020, and that much higher transmission rates have probably occurred in a number of Latin American countries. This simple modelling framework can help countries to assess the progression of the pandemic and can be applied in any scenario for which reliable age-specific death data are available.
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Envelhecimento/imunologia , Teste Sorológico para COVID-19/estatística & dados numéricos , COVID-19/imunologia , COVID-19/mortalidade , Internacionalidade , Pandemias/estatística & dados numéricos , SARS-CoV-2/imunologia , Adolescente , Adulto , Distribuição por Idade , Fatores Etários , Idoso , Idoso de 80 Anos ou mais , COVID-19/virologia , Criança , Pré-Escolar , Feminino , Humanos , Lactente , Recém-Nascido , Masculino , Pessoa de Meia-Idade , Adulto JovemRESUMO
Infants less than 1 y of age experience high rates of dengue disease in dengue virus (DENV) endemic countries. This burden is commonly attributed to antibody-dependent enhancement (ADE), whereby concentrations of maternally derived DENV antibodies become subneutralizing, and infection-enhancing. Understanding antibody-related mechanisms of enhanced infant dengue disease risk represents a significant challenge due to the dynamic nature of antibodies and their imperfect measurement processes. Further, key uncertainties exist regarding the impact of long-term shifts in birth rates, population-level infection risks, and maternal ages on the DENV immune landscape of newborns and their subsequent risks of severe dengue disease in infancy. Here, we analyze DENV antibody data from two infant cohorts (N = 142 infants with 605 blood draws) and 40 y of infant dengue hospitalization data from Thailand. We use mathematical models to reconstruct maternally derived antibody dynamics, accounting for discretized measurement processes and limits of assay detection. We then explore possible antibody-related mechanisms of enhanced infant dengue disease risk and their ability to reconstruct the observed age distribution of hospitalized infant dengue cases. We find that ADE mechanisms are best able to reconstruct the observed data. Finally, we describe how the shifting epidemiology of dengue in Thailand, combined with declining birth rates, have decreased the absolute risk of infant dengue disease by 88% over a 40-y period while having minimal impact on the mean age of infant hospitalized dengue disease.
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Vírus da Dengue , Dengue , Dengue Grave , Humanos , Lactente , Recém-Nascido , Anticorpos Antivirais , Anticorpos Neutralizantes , Anticorpos FacilitadoresRESUMO
The spatial distribution of dengue and its vectors (spp. Aedes) may be the widest it has ever been, and projections suggest that climate change may allow the expansion to continue. However, less work has been done to understand how climate variability and change affects dengue in regions where the pathogen is already endemic. In these areas, the waxing and waning of immunity has a large impact on temporal dynamics of cases of dengue haemorrhagic fever. Here, we use 51 years of data across 72 provinces and characterise spatiotemporal patterns of dengue in Thailand, where dengue has caused almost 1.5 million cases over the last 30 years, and examine the roles played by temperature and dynamics of immunity in giving rise to those patterns. We find that timescales of multiannual oscillations in dengue vary in space and time and uncover an interesting spatial phenomenon: Thailand has experienced multiple, periodic synchronisation events. We show that although patterns in synchrony of dengue are similar to those observed in temperature, the relationship between the two is most consistent during synchronous periods, while during asynchronous periods, temperature plays a less prominent role. With simulations from temperature-driven models, we explore how dynamics of immunity interact with temperature to produce the observed patterns in synchrony. The simulations produced patterns in synchrony that were similar to observations, supporting an important role of immunity. We demonstrate that multiannual oscillations produced by immunity can lead to asynchronous dynamics and that synchrony in temperature can then synchronise these dengue dynamics. At higher mean temperatures, immune dynamics can be more predominant, and dengue dynamics more insensitive to multiannual fluctuations in temperature, suggesting that with rising mean temperatures, dengue dynamics may become increasingly asynchronous. These findings can help underpin predictions of disease patterns as global temperatures rise.
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Dengue , Epidemias , Dengue/epidemiologia , Humanos , Incidência , Mosquitos Vetores , Temperatura , Tailândia/epidemiologiaRESUMO
The mean age of dengue hemorrhagic fever (DHF) cases increased considerably in Thailand from 8.1 to 24.3 y between 1981 and 2017 (mean annual increase of 0.45 y). Alternative proposed explanations for this trend, such as changes in surveillance practices, reduced mosquitohuman contact, and shifts in population demographics, have different implications for global dengue epidemiology. To evaluate the contribution of each of these hypothesized mechanisms to the observed data, we developed 20 nested epidemiological models of dengue virus infection, allowing for variation over time in population demographics, infection hazards, and reporting rates. We also quantified the effect of removing or retaining each source of variation in simulations of the age trajectory. Shifts in the age structure of susceptibility explained 58% of the observed change in age. Adding heterogeneous reporting by age and reductions in per-serotype infection hazard to models with shifts in susceptibility explained an additional 42%. Reductions in infection hazards were mostly driven by changes in the number of infectious individuals at any time (another consequence of shifting age demographics) rather than changes in the transmissibility of individual infections. We conclude that the demographic transition drives the overwhelming majority of the observed change as it changes both the age structure of susceptibility and the number of infectious individuals. With the projected Thai population age structure, our results suggest a continuing increase in age of DHF cases, shifting the burden toward individuals with more comorbidity. These insights into dengue epidemiology may be relevant to many regions of the globe currently undergoing comparable changes in population demographics.
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Dengue , Dinâmica Populacional , Idoso , Dengue/diagnóstico , Dengue/epidemiologia , Humanos , Saúde Pública , Tailândia/epidemiologiaRESUMO
We developed mathematical models to analyze a large dengue virus (DENV) epidemic in Reunion Island in 2018-2019. Our models captured major drivers of uncertainty including the complex relationship between climate and DENV transmission, temperature trends, and underreporting. Early assessment correctly concluded that persistence of DENV transmission during the austral winter 2018 was likely and that the second epidemic wave would be larger than the first one. From November 2018, the detection probability was estimated at 10%-20% and, for this range of values, our projections were found to be remarkably accurate. Overall, we estimated that 8% and 18% of the population were infected during the first and second wave, respectively. Out of the 3 models considered, the best-fitting one was calibrated to laboratory entomological data, and accounted for temperature but not precipitation. This study showcases the contribution of modeling to strengthen risk assessments and planning of national and local authorities.
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Aedes , Vírus da Dengue , Dengue , Epidemias , Animais , Humanos , Reunião/epidemiologia , Tempo (Meteorologia)RESUMO
BACKGROUND: Nipah virus (NiV), a highly lethal virus in humans, circulates in Pteropus bats throughout South and Southeast Asia. Difficulty in obtaining viral genomes from bats means we have a poor understanding of NiV diversity. METHODS: We develop phylogenetic approaches applied to the most comprehensive collection of genomes to date (N=257, 175 from bats, 73 from humans) from six countries over 22 years (1999-2020). We divide the four major NiV sublineages into 15 genetic clusters. Using Approximate Bayesian Computation fit to a spatial signature of viral diversity, we estimate the presence and the average size of genetic clusters per area. RESULTS: We find that, within any bat roost, there are an average of 2.4 co-circulating genetic clusters, rising to 5.5 clusters at areas of 1500-2000km2. We estimate that each genetic cluster occupies an average area of 1.3million km2 (95%CI: 0.6-2.3 million), with 14 clusters in an area of 100,000km2 (95%CI: 6-24). In the few sites in Bangladesh and Cambodia where genomic surveillance has been concentrated, we estimate that most clusters have been identified, but only â¼15% of overall NiV diversity has been uncovered. CONCLUSION: Our findings are consistent with entrenched co-circulation of distinct lineages, even within roosts, coupled with slow migration over larger spatial scales.
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BACKGROUND: Dengue virus (DENV) non-structural protein 1 (NS1) has multiple functions within infected cells, on the cell surface, and in secreted form, and is highly immunogenic. Immunity from previous DENV infections is known to exert both positive and negative effects on subsequent DENV infections, but the contribution of NS1-specific antibodies to these effects is incompletely understood. METHODS: We investigated the functions of NS1-specific antibodies and their significance in DENV infection. We analyzed plasma samples collected in a prospective cohort study prior to symptomatic or subclinical secondary DENV infection. We measured binding to purified recombinant NS1 protein and to NS1-expressing CEM cells, antibody-mediated NK cell activation by plate-bound NS1 protein, and antibody-dependent cellular cytotoxicity (ADCC) of NS1-expressing target cells. RESULTS: We found that antibody responses to NS1 were highly serotype-cross-reactive and that subjects who experienced subclinical DENV infection had significantly higher antibody responses to NS1 in pre-infection plasma than subjects who experienced symptomatic infection. We observed strong positive correlations between antibody binding and NK activation. CONCLUSIONS: These findings demonstrate the involvement of NS1-specific antibodies in ADCC and provide evidence for a protective effect of NS1-specific antibodies in secondary DENV infection.
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There is an increasing global burden from chikungunya virus (CHIKV). Bangladesh reported a major epidemic in 2017, however, it was unclear if there had been prior widespread transmission. We conducted a nationally representative seroprevalence survey in 70 randomly selected communities immediately prior to the epidemic. We found 69/2,938 (2.4%) of sampled individuals were seropositive to CHIKV. Being seropositive to dengue virus (aOR 3.13 [95% CIs: 1.86-5.27]), male sex (aOR 0.59 [95% CIs: 0.36-0.99]), and community presence of Aedes aegypti mosquitoes (aOR: 1.80, 95% CI: 1.05-3.07) were significantly associated with CHIKV seropositivity. Using a spatial prediction model, we estimated that across the country, 4.99 (95% CI: 4.89 - 5.08) million people had been previously infected. These findings highlight high population susceptibility prior to the major outbreak and that previous outbreaks must have been spatially isolated.
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Neutralizing antibodies are important correlates of protection against dengue. Yet, determinants of variation in neutralization across strains within the four dengue virus serotypes (DENV1-4) is imperfectly understood. Studies focus on structural DENV proteins, especially the envelope (E), the primary target of anti-DENV antibodies. Although changes in immune recognition (antigenicity) are often attributed to variation in epitope residues, viral processes influencing conformation and epitope accessibility also affect neutralizability, suggesting possible modulating roles of nonstructural proteins. We estimated effects of residue changes in all 10 DENV proteins on antigenic distances between 348 DENV collected from individuals living in Bangkok, Thailand (1994-2014). Antigenic distances were derived from response of each virus to a panel of twenty non-human primate antisera. Across 100 estimations, excluding 10% of virus pairs each time, 77 of 295 positions with residue variability in E consistently conferred antigenic effects; 52 were within ±3 sites of known binding sites of neutralizing human monoclonal antibodies, exceeding expectations from random assignments of effects to sites (p = 0.037). Effects were also identified for 16 sites on the stem/anchor of E which were only recently shown to become exposed under physiological conditions. For all proteins, except nonstructural protein 2A (NS2A), root-mean-squared-error (RMSE) in predicting distances between pairs held out in each estimation did not outperform sequences of equal length derived from all proteins or E, suggesting that antigenic signals present were likely through linkage with E. Adjusted for E, we identified 62/219 sites embedding the excess signals in NS2A. Concatenating these sites to E additionally explained 3.4% to 4.0% of observed variance in antigenic distances compared to E alone (50.5% to 50.8%); RMSE outperformed concatenating E with sites from any protein of the virus (ΔRMSE, 95%IQR: 0.01, 0.05). Our results support examining antigenic determinants beyond the DENV surface.
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Vírus da Dengue , Dengue , Aminoácidos , Animais , Anticorpos Monoclonais , Anticorpos Neutralizantes , Anticorpos Antivirais , Epitopos/genética , Tailândia , Proteínas do Envelope ViralRESUMO
China had conducted some of the most stringent public health measures to control the spread of successive SARS-CoV-2 variants. However, the effectiveness of these measures and their impacts on the associated disease burden have rarely been quantitatively assessed at the national level. To address this gap, we developed a stochastic age-stratified metapopulation model that incorporates testing, contact tracing and isolation, based on 419 million travel movements among 366 Chinese cities. The study period for this model began from September 2022. The COVID-19 disease burden was evaluated, considering 8 types of underlying health conditions in the Chinese population. We identified the marginal effects between the testing speed and reduction in the epidemic duration. The findings suggest that assuming a vaccine coverage of 89%, the Omicron-like wave could be suppressed by 3-day interval population-level testing (PLT), while it would become endemic with 4-day interval PLT, and without testing, it would result in an epidemic. PLT conducted every 3 days would not only eliminate infections but also keep hospital bed occupancy at less than 29.46% (95% CI, 22.73-38.68%) of capacity for respiratory illness and ICU bed occupancy at less than 58.94% (95% CI, 45.70-76.90%) during an outbreak. Furthermore, the underlying health conditions would lead to an extra 2.35 (95% CI, 1.89-2.92) million hospital admissions and 0.16 (95% CI, 0.13-0.2) million ICU admissions. Our study provides insights into health preparedness to balance the disease burden and sustainability for a country with a population of billions.
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COVID-19 , Epidemias , Humanos , COVID-19/epidemiologia , COVID-19/prevenção & controle , SARS-CoV-2 , Saúde Pública , Epidemias/prevenção & controle , China/epidemiologiaRESUMO
As with many pathogens, most dengue infections are subclinical and therefore unobserved 1 . Coupled with limited understanding of the dynamic behaviour of potential serological markers of infection, this observational problem has wide-ranging implications, including hampering our understanding of individual- and population-level correlates of infection and disease risk and how these change over time, between assay interpretations and with cohort design. Here we develop a framework that simultaneously characterizes antibody dynamics and identifies subclinical infections via Bayesian augmentation from detailed cohort data (3,451 individuals with blood draws every 91 days, 143,548 haemagglutination inhibition assay titre measurements)2,3. We identify 1,149 infections (95% confidence interval, 1,135-1,163) that were not detected by active surveillance and estimate that 65% of infections are subclinical. After infection, individuals develop a stable set point antibody load after one year that places them within or outside a risk window. Individuals with pre-existing titres of ≤1:40 develop haemorrhagic fever 7.4 (95% confidence interval, 2.5-8.2) times more often than naive individuals compared to 0.0 times for individuals with titres >1:40 (95% confidence interval: 0.0-1.3). Plaque reduction neutralization test titres ≤1:100 were similarly associated with severe disease. Across the population, variability in the size of epidemics results in large-scale temporal changes in infection and disease risk that correlate poorly with age.
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Anticorpos Antivirais/imunologia , Dengue/imunologia , Dengue/transmissão , Suscetibilidade a Doenças , Adolescente , Anticorpos Antivirais/sangue , Teorema de Bayes , Criança , Estudos de Coortes , Dengue/sangue , Vacinas contra Dengue/imunologia , Testes de Inibição da Hemaglutinação , Humanos , Modelos Biológicos , Risco , Estações do AnoRESUMO
BACKGROUND: Household transmission studies inform how viruses spread among close contacts, but few characterize household transmission of endemic coronaviruses. METHODS: We used data collected from 223 households with school-age children participating in weekly disease surveillance over 2 respiratory virus seasons (December 2015 to May 2017), to describe clinical characteristics of endemic human coronaviruses (HCoV-229E, HcoV-HKU1, HcoV-NL63, HcoV-OC43) infections, and community and household transmission probabilities using a chain-binomial model correcting for missing data from untested households. RESULTS: Among 947 participants in 223 households, we observed 121 infections during the study, most commonly subtype HCoV-OC43. Higher proportions of infected children (<19 years) displayed influenza-like illness symptoms than infected adults (relative risk, 3.0; 95% credible interval [CrI], 1.5-6.9). The estimated weekly household transmission probability was 9% (95% CrI, 6-13) and weekly community acquisition probability was 7% (95% CrI, 5-10). We found no evidence for differences in community or household transmission probabilities by age or symptom status. Simulations suggest that our study was underpowered to detect such differences. CONCLUSIONS: Our study highlights the need for large household studies to inform household transmission, the challenges in estimating household transmission probabilities from asymptomatic individuals, and implications for controlling endemic CoVs.
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Coronavirus Humano 229E , Infecções por Coronavirus , Coronavirus Humano NL63 , Coronavirus Humano OC43 , Infecções Respiratórias , Vírus , Criança , Adulto , Humanos , Estações do AnoRESUMO
Chikungunya virus (CHIKV) is a major public health concern worldwide. However, infection levels are rarely known, especially in Africa. We recruited individuals from Ouagadougou, Burkina Faso and Lambaréné, Gabon (age range, 1-55 years), tested their blood for CHIKV antibodies, and used serocatalytic models to reconstruct epidemiological histories. In Ouagadougou, 291 of 999 (29.1%) individuals were seropositive, ranging from 2% among those aged <10 years to 66% in those aged 40-55 years. We estimated there were 7 outbreaks since the 1970s but none since 2001, resulting in 600 000 infections in the city, none of which were reported. However, we could not definitively conclude whether infections were due to CHIKV or o'nyong-nyong, another alphavirus. In Lambaréné, 117 of 427 (27%) participants were seropositive. Our model identified a single outbreak sometime since 2007, consistent with the only reported CHIKV outbreak in the country. These findings suggest sporadic outbreaks in these settings and that the burden remains undetected or incorrectly attributed.
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Febre de Chikungunya , Vírus Chikungunya , Humanos , Lactente , Pré-Escolar , Criança , Adolescente , Adulto Jovem , Adulto , Pessoa de Meia-Idade , Febre de Chikungunya/epidemiologia , Gabão/epidemiologia , Burkina Faso/epidemiologia , Surtos de DoençasRESUMO
BACKGROUND: Over the last decades, enormous successes have been achieved in reducing malaria burden globally. In Latin America, South East Asia, and the Western Pacific, many countries now pursue the goal of malaria elimination by 2030. It is widely acknowledged that Plasmodium spp. infections cluster spatially so that interventions need to be spatially informed, e.g. spatially targeted reactive case detection strategies. Here, the spatial signature method is introduced as a tool to quantify the distance around an index infection within which other infections significantly cluster. METHODS: Data were considered from cross-sectional surveys from Brazil, Thailand, Cambodia, and Solomon Islands, conducted between 2012 and 2018. Household locations were recorded by GPS and finger-prick blood samples from participants were tested for Plasmodium infection by PCR. Cohort studies from Brazil and Thailand with monthly sampling over a year from 2013 until 2014 were also included. The prevalence of PCR-confirmed infections was calculated at increasing distance around index infections (and growing time intervals in the cohort studies). Statistical significance was defined as prevalence outside of a 95%-quantile interval of a bootstrap null distribution after random re-allocation of locations of infections. RESULTS: Prevalence of Plasmodium vivax and Plasmodium falciparum infections was elevated in close proximity around index infections and decreased with distance in most study sites, e.g. from 21.3% at 0 km to the global study prevalence of 6.4% for P. vivax in the Cambodian survey. In the cohort studies, the clustering decreased with longer time windows. The distance from index infections to a 50% reduction of prevalence ranged from 25 m to 3175 m, tending to shorter distances at lower global study prevalence. CONCLUSIONS: The spatial signatures of P. vivax and P. falciparum infections demonstrate spatial clustering across a diverse set of study sites, quantifying the distance within which the clustering occurs. The method offers a novel tool in malaria epidemiology, potentially informing reactive intervention strategies regarding radius choices of operations around detected infections and thus strengthening malaria elimination endeavours.
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Malária Falciparum , Malária Vivax , Humanos , Plasmodium vivax , Estudos Transversais , Plasmodium falciparum , Análise por Conglomerados , Estudos de CoortesRESUMO
BACKGROUND: Aedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical models combine data from multiple locations and use links with environmental and socioeconomic factors to make predictive risk maps. Here we systematically review past approaches to map risk for different Aedes-borne arboviruses from local to global scales, identifying differences and similarities in the data types, covariates, and modelling approaches used. METHODS: We searched on-line databases for predictive risk mapping studies for dengue, Zika, chikungunya, and yellow fever with no geographical or date restrictions. We included studies that needed to parameterise or fit their model to real-world epidemiological data and make predictions to new spatial locations of some measure of population-level risk of viral transmission (e.g. incidence, occurrence, suitability, etc.). RESULTS: We found a growing number of arbovirus risk mapping studies across all endemic regions and arboviral diseases, with a total of 176 papers published 2002-2022 with the largest increases shortly following major epidemics. Three dominant use cases emerged: (i) global maps to identify limits of transmission, estimate burden and assess impacts of future global change, (ii) regional models used to predict the spread of major epidemics between countries and (iii) national and sub-national models that use local datasets to better understand transmission dynamics to improve outbreak detection and response. Temperature and rainfall were the most popular choice of covariates (included in 50% and 40% of studies respectively) but variables such as human mobility are increasingly being included. Surprisingly, few studies (22%, 31/144) robustly tested combinations of covariates from different domains (e.g. climatic, sociodemographic, ecological, etc.) and only 49% of studies assessed predictive performance via out-of-sample validation procedures. CONCLUSIONS: Here we show that approaches to map risk for different arboviruses have diversified in response to changing use cases, epidemiology and data availability. We identify key differences in mapping approaches between different arboviral diseases, discuss future research needs and outline specific recommendations for future arbovirus mapping.
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Aedes , Infecções por Arbovirus , Arbovírus , Febre de Chikungunya , Dengue , Febre Amarela , Infecção por Zika virus , Zika virus , Animais , Humanos , Infecções por Arbovirus/epidemiologia , Febre Amarela/epidemiologia , Mosquitos Vetores , Dengue/epidemiologiaRESUMO
BACKGROUND: Dengue virus (DENV) often circulates endemically. In such settings with high levels of transmission, it remains unclear whether there are risk factors that alter individual infection risk. METHODS: We tested blood taken from individuals living in multigenerational households in Kamphaeng Phet province, Thailand for DENV antibodies (N = 2364, mean age 31 years). Seropositivity ranged from 45.4% among those 1-5 years old to 99.5% for those >30 years. Using spatially explicit catalytic models, we estimated that 11.8% of the susceptible population gets infected annually. RESULTS: We found that 37.5% of the variance in seropositivity was explained by unmeasured household-level effects with only 4.2% explained by spatial differences between households. The serostatus of individuals from the same household remained significantly correlated even when separated by up to 15 years in age. CONCLUSIONS: These findings show that despite highly endemic transmission, persistent differences in infection risk exist across households, the reasons for which remain unclear.
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Vírus da Dengue , Dengue , Adulto , Pré-Escolar , Suscetibilidade a Doenças , Características da Família , Humanos , Lactente , Tailândia/epidemiologiaRESUMO
BACKGROUND: Nipah virus is a highly virulent zoonotic pathogen that can be transmitted between humans. Understanding the dynamics of person-to-person transmission is key to designing effective interventions. METHODS: We used data from all Nipah virus cases identified during outbreak investigations in Bangladesh from April 2001 through April 2014 to investigate case-patient characteristics associated with onward transmission and factors associated with the risk of infection among patient contacts. RESULTS: Of 248 Nipah virus cases identified, 82 were caused by person-to-person transmission, corresponding to a reproduction number (i.e., the average number of secondary cases per case patient) of 0.33 (95% confidence interval [CI], 0.19 to 0.59). The predicted reproduction number increased with the case patient's age and was highest among patients 45 years of age or older who had difficulty breathing (1.1; 95% CI, 0.4 to 3.2). Case patients who did not have difficulty breathing infected 0.05 times as many contacts (95% CI, 0.01 to 0.3) as other case patients did. Serologic testing of 1863 asymptomatic contacts revealed no infections. Spouses of case patients were more often infected (8 of 56 [14%]) than other close family members (7 of 547 [1.3%]) or other contacts (18 of 1996 [0.9%]). The risk of infection increased with increased duration of exposure of the contacts (adjusted odds ratio for exposure of >48 hours vs. ≤1 hour, 13; 95% CI, 2.6 to 62) and with exposure to body fluids (adjusted odds ratio, 4.3; 95% CI, 1.6 to 11). CONCLUSIONS: Increasing age and respiratory symptoms were indicators of infectivity of Nipah virus. Interventions to control person-to-person transmission should aim to reduce exposure to body fluids. (Funded by the National Institutes of Health and others.).
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Infecções por Henipavirus/transmissão , Vírus Nipah , Adolescente , Adulto , Fatores Etários , Animais , Bangladesh/epidemiologia , Líquidos Corporais/virologia , Criança , Busca de Comunicante , Transmissão de Doença Infecciosa/prevenção & controle , Feminino , Infecções por Henipavirus/epidemiologia , Infecções por Henipavirus/prevenção & controle , Humanos , Masculino , Pessoa de Meia-Idade , Fatores de Risco , Adulto Jovem , Zoonoses/transmissãoRESUMO
IntroductionSARS-CoV-2, the virus that causes COVID-19, has spread rapidly worldwide. In January 2020, a surveillance system was implemented in France for early detection of cases and their contacts to help limit secondary transmissions.AimTo use contact-tracing data collected during the initial phase of the COVID-19 pandemic to better characterise SARS-CoV-2 transmission.MethodsWe analysed data collected during contact tracing and retrospective epidemiological investigations in France from 24 January to 30 March 2020. We assessed the secondary clinical attack rate and characterised the risk of a contact becoming a case. We described chains of transmission and estimated key parameters of spread.ResultsDuring the study period, 6,082 contacts of 735 confirmed cases were traced. The overall secondary clinical attack rate was 4.1% (95% confidence interval (CI): 3.6-4.6), increasing with age of index case and contact. Compared with co-workers/friends, family contacts were at higher risk of becoming cases (adjusted odds ratio (AOR): 2.1, 95% CI: 1.4-3.0) and nosocomial contacts were at lower risk (AOR: 0.3, 95% CI: 0.1-0.7). Of 328 infector/infectee pairs, 49% were family members. The distribution of secondary cases was highly over-dispersed: 80% of secondary cases were caused by 10% of cases. The mean serial interval was 5.1 days (interquartile range (IQR): 2-8 days) in contact tracing pairs, where late transmission events may be censored, and 6.8 (3-8) days in pairs investigated retrospectively.ConclusionThis study increases knowledge of SARS-CoV-2 transmission, including the importance of superspreading events during the onset of the pandemic.
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COVID-19 , Busca de Comunicante , Humanos , Pandemias , Estudos Retrospectivos , SARS-CoV-2RESUMO
BACKGROUND: Hepatitis E virus (HEV) genotypes 1 and 2 are a major cause of avoidable morbidity and mortality in South Asia. Despite the high risk of death among infected pregnant women, scarce incidence data has been a contributing factor to global policy recommendations against the introduction of licensed hepatitis E vaccines, one of the only effective prevention tools. METHODS: We tested serum from a nationally representative serosurvey in Bangladesh for anti-HEV immunoglobulin G and estimated seroprevalence. We used Bayesian geostatistical models to generate high-resolution maps of seropositivity and examined variability in seropositivity by individual-level, household-level, and community-level risk factors using spatial logistic regression. RESULTS: We tested serum samples from 2924 individuals from 70 communities representing all divisions of Bangladesh and estimated a national seroprevalence of 20% (95% confidence interval [CI], 17%-24%). Seropositivity increased with age and male sex (odds ratio, 2.2 male vs female; 95% CI, 1.8-2.8). Community-level seroprevalence ranged widely (0-78%) with higher seroprevalence in urban areas, including Dhaka, with a 3.0-fold (95% credible interval, 2.3-3.7) higher seroprevalence than the rest of the country. CONCLUSIONS: Hepatitis E infections are common throughout Bangladesh. Strengthening surveillance for hepatitis E, especially in urban areas, can provide additional evidence to appropriately target interventions.