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In this work, we obtained a general formulation for the mating probability and fertile egg production in helminth parasites, focusing on the reproductive behavior of polygamous parasites and its implications for transmission dynamics. By exploring various reproductive variables in parasites with density-dependent fecundity, such as helminth parasites, we departed from the traditional assumptions of Poisson and negative binomial distributions to adopt an arbitrary distribution model. Our analysis considered critical factors such as mating probability, fertile egg production, and the distribution of female and male parasites among hosts, whether they are distributed together or separately. We show that the distribution of parasites within hosts significantly influences transmission dynamics, with implications for parasite persistence and, therefore, with implications in parasite control. Using statistical models and empirical data from Monte Carlo simulations, we provide insights into the complex interplay of reproductive variables in helminth parasites, enhancing our understanding of parasite dynamics and the transmission of parasitic diseases.

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Background: COVID-19 dynamics are driven by a complex interplay of factors including population behaviour, new variants, vaccination and immunity from prior infections. We quantify drivers of SARS-CoV-2 transmission in the Dominican Republic, an upper-middle income country of 10.8 million people. We then assess the impact of the vaccination campaign implemented in February 2021, primarily using CoronaVac, in saving lives and averting hospitalisations. Methods: We fit an age-structured, multi-variant transmission dynamic model to reported deaths, hospital bed occupancy, and seroprevalence data until December 2021, and simulate epidemic trajectories under different counterfactual scenarios. Findings: We estimate that vaccination averted 7210 hospital admissions (95% credible interval, CrI: 6830-7600), 2180 intensive care unit admissions (95% CrI: 2080-2280) and 766 deaths (95% CrI: 694-859) in the first 6 months of the campaign. If no vaccination had occurred, we estimate that an additional decrease of 10-20% in population mobility would have been required to maintain equivalent death and hospitalisation outcomes. We also found that early vaccination with CoronaVac was preferable to delayed vaccination using a product with higher efficacy. Interpretation: SARS-CoV-2 transmission dynamics in the Dominican Republic were driven by a substantial accumulation of immunity during the first two years of the pandemic but, despite this, vaccination was essential in enabling a return to pre-pandemic mobility levels without considerable additional morbidity and mortality. Funding: Medical Research Council, Wellcome Trust, Royal Society, US CDC and Australian National Health and Medical Research Council.

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Background: Household transmission studies seek to understand the transmission dynamics of a pathogen by estimating the risk of infection from household contacts and community exposures. We estimated within/extra-household SARS-CoV-2 infection risk and associated factors in a household cohort study in one of the most vulnerable neighbourhoods in Rio de Janeiro city. Methods: Individuals ≥1 years-old with suspected or confirmed COVID-19 in the past 30 days (index cases) and household members aged ≥1 year were enrolled and followed at 14 and 28 days (study period November/2020-December/2021). RT-PCR testing, COVID-19 symptoms, and SARS-CoV-2 serologies were ascertained in all visits. Chain binomial household transmission models were fitted using data from 2024 individuals (593 households). Findings: Extra-household infection risk was 74.2% (95% credible interval [CrI] 70.3-77.8), while within-household infection risk was 11.4% (95% CrI 5.7-17.2). Participants reporting having received two doses of a COVID-19 vaccine had lower extra-household (68.9%, 95% CrI 57.3-77.6) and within-household (4.1%, 95% CrI 0.4-16.6) infection risk. Within-household infection risk was higher among participants aged 10-19 years, from overcrowded households, and with low family income. Contrastingly, extra-household infection risk was higher among participants aged 20-29 years, unemployed, and public transportation users. Interpretation: Our study provides important insights into COVID-19 household/community transmission in a vulnerable population that resided in overcrowded households and who struggled to adhere to lockdown policies and social distancing measures. The high extra-household infection risk highlights the extreme social vulnerability of this population. Prioritising vaccination of the most socially vulnerable could protect these individuals and reduce widespread community transmission. Funding: Fundação Oswaldo Cruz, CNPq, FAPERJ, Royal Society, Instituto Serrapilheira, FAPESP.

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AIMS: Protozoan and helminth parasitic infections pose significant public health challenges, especially in developing countries with rural populations marked by suboptimal hygiene practices and socio-economic constraints. The parasites are the etiological agents of these infections and have a notably elevated global prevalence. Therefore, this study focuses on estimating the frequency and transmission dynamics of several parasitic species, including Blastocystis, Giardia, Cryptosporidium spp., Entamoeba histolytica, Ascaris lumbricoides, Trichuris trichiura, Taenia spp. and hookworms, within a rural community in southwest Colombia with a particular emphasis on the One Health framework, considering environmental and zoonotic transmission potentials. METHODS AND RESULTS: This study involved the analysis of 125 samples, encompassing human participants (n = 99), their domestic pets (dogs) (n = 24) and water sources (n = 2). Parasite detection was carried out utilizing a combination of microscopy and molecular techniques. Furthermore, the characterization of Blastocystis subtypes (STs) was achieved through Oxford Nanopore sequencing of the rRNA-18S gene. The investigation also entailed the examination of potential associations between intestinal parasitism and various sociodemographic factors. Results revealed a high frequency of parasitic infections when employing molecular methods, with Blastocystis (n = 109/87%), Giardia (n = 20/16%), Ancylostoma duodenale (n = 28/22%), Ancylostoma ceylanicum (n = 7/5.6%), E. histolytica (n = 6/4.8%), Cryptosporidium spp. (n = 12/9.6%) and even Taenia (n = 1/0.8%) detected. Cryptosporidium spp. was also identified in water samples. Coinfections were prevalent, with 57% (n = 70) of samples exhibiting single-parasite infections and 43% (n = 53) showing various degrees of polyparasitism, emphasizing the complexity of transmission dynamics. Blastocystis subtyping, conducted via Oxford Nanopore sequencing, revealed a diversity of subtypes and coexistence patterns, with ST2 being the most prevalent. CONCLUSIONS: This research underscores the importance of using molecular techniques for frequency estimation, particularly emphasizing the relevance of zoonotic transmission in parasitic infections. It highlights the significance of the One Health approach in comprehending the circulation of parasites among animals, humans and environmental sources, thereby directly impacting public health and epidemiological surveillance.

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The Zika virus (ZIKV) is a serious global public health crisis. A major control challenge is its multiple transmission modes. This paper aims to simulate the transmission patterns of ZIKV using a dynamic process-based epidemiological model written in ordinary differential equations, which incorporates the human-to-mosquito infection by bites and sewage, mosquito-to-human infection by bites, and human-to-human infection by sex. Mathematical analyses are carried out to calculate the basic reproduction number and backward bifurcation, and prove the existence and stability of the equilibria. The model is validated with infection data by applying it to the 2015-2016 ZIKV epidemic in Brazil. The results indicate that the reproduction number is estimated to be 2.13, in which the contributions by mosquito bite, sex and sewage account for 85.7%, 3.5% and 10.8%, respectively. This number and the morbidity rate are most sensitive to parameters related to mosquito ecology, rather than asymptomatic or human-to-human transmission. Multiple transmission routes and suitable temperature exacerbate ZIKV infection in Brazil, and the vast majority of human infection cases were prevented by the intervention implemented. These findings may provide new insights to improve the risk assessment of ZIKV infection.

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The Coronavirus Disease 2019 (COVID-19) is a zoonotic disease caused by the pandemic virus SARS-CoV-2. Domestic and wild animals are susceptible to infection and are potential reservoirs for virus variants. To date, there is no information about the exposure of companion animals in Buenos Aires Suburbs, the area with the largest population in Argentina where the highest number of COVID-19 human cases occurred during the first infection wave. Here we developed a multi-species indirect ELISA to measure antibodies reactive to the SARS-CoV-2 receptor-binding domain (RBD) from several vertebrates constituting the class Mammalia, making it a valuable tool for field serosurveillance. The ELISA cut-off value was estimated by sera from dogs, cats, cattle, and pigs sampled before 2019 (n = 170), considering a 98% percentile and a grey zone to completely exclude any false positive result. Specificity was confirmed by measuring levels of neutralizing antibodies against canine coronavirus, the avidity of specific antibodies, and their capacity to impede the binding of a recombinant RBD protein to VERO cells in an In-Cell ELISA. Sera from 464 cats and dogs sampled in 2020 and 2021 ("pandemic" samples) were assessed using the RBD-ELISA. Information on COVID-19 disease in the household and the animals' lifestyles was collected. In Buenos Aires Suburbs cats were infected at a higher proportion than dogs, seroprevalence was 7.1 and 1.68%, respectively. Confirmed COVID-19 in the caregivers and outdoor lifestyle were statistically associated with seropositivity in cats. The risk of cats getting infected living indoors in COVID-19-negative households was null. The susceptibility of mammals to SARS-CoV-2, the possibility of transmission between animals themselves and humans, together with the free-roaming lifestyle typical of Buenos Aires suburban companion animals, urge pursuing responsible animal care and avoiding human interaction with animals during the disease course. The multi-species RBD-ELISA we developed can be used as a tool for serosurveillance of SARS-CoV-2 infection in mammalians (domestic and wild), guiding further targeted virological analyses to encounter susceptible species, interspecies transmission, and potential virus reservoirs in our region.

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The study of HIV-1 transmission networks inferred from viral genetic data can be used to clarify important factors about the dynamics of HIV-1 transmission, such as network growth rate and demographic composition. In Brazil, HIV transmission has been stable since the early 2000s and the study of transmission clusters can provide valuable data to understand the drivers of virus spread. In this work, we analyzed a nation-wide database of approximately 53,000 HIV-1 nucleotide pol sequences sampled from genotyped patients from 2008-2017. Phylogenetic trees were reconstructed for the HIV-1 subtypes B, C and F1 in Brazil and transmission clusters were inferred by applying genetic distances thresholds of 1.5%, 3.0% and 4.5%, as well as high (>0.9) cluster statistical support. An odds ratio test revealed that young men (15-24 years) and individuals with more years of education presented higher odds to cluster. The assortativity coefficient revealed that individuals with similar demographic features tended to cluster together, with emphasis on features, such as place of residence and age. We also observed that assortativity weakens as the genetic distance threshold increases. Our results indicate that the phylogenetic clusters identified here are likely representative of the contact networks that shape HIV transmission, and this is a valuable tool even in sites with low sampling density, such as Brazil.

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Salmonella enterica can survive in surface waters (SuWa), and the role of nonhost environments in its transmission has acquired increasing relevance. In this study, we conducted comparative genomic analyses of 172 S. enterica isolates collected from SuWa across 3 months in six states of central Mexico during 2019. S. enterica transmission dynamics were assessed using 87 experimental and 112 public isolates from Mexico collected during 2002 through 2019. We also studied genetic relatedness between SuWa isolates and human clinical strains collected in North America during 2005 through 2020. Among experimental isolates, we identified 41 S. enterica serovars and 56 multilocus sequence types (STs). Predominant serovars were Senftenberg (n = 13), Meleagridis, Agona, and Newport (n = 12 each), Give (n = 10), Anatum (n = 8), Adelaide (n = 7), and Infantis, Mbandaka, Ohio, and Typhimurium (n = 6 each). We observed a high genetic diversity in the sample under study, as well as clonal dissemination of strains across distant regions. Some of these strains are epidemiologically important (ST14, ST45, ST118, ST132, ST198, and ST213) and were genotypically close to those involved in clinical cases in North America. Transmission network analysis suggests that SuWa are a relevant source of S. enterica (0.7 source/hub ratio) and contribute to its dissemination as isolates from varied sources and clinical cases have SuWa isolates as common ancestors. Overall, the study shows that SuWa act as reservoirs of various S. enterica serovars of public health significance. Further research is needed to better understand the mechanisms involved in SuWa contamination by S. enterica, as well as to develop interventions to contain its dissemination in food production settings. IMPORTANCE Surface waters are heavily used in food production worldwide. Several human pathogens can survive in these waters for long periods and disseminate to food production environments, contaminating our food supply. One of these pathogens is Salmonella enterica, a leading cause of foodborne infections, hospitalizations, and deaths in many countries. This research demonstrates the role of surface waters as a vehicle for the transmission of Salmonella along food production chains. It also shows that some strains circulating in surface waters are very similar to those implicated in human infections and harbor genes that confer resistance to multiple antibiotics, posing a risk to public health. This study contributes to expand our current knowledge on the ecology and epidemiology of Salmonella in surface waters.

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BACKGROUND: Our aim was to study the association between case rates and reductions in urban mobility in state capitals of Colombia. METHODS: We designed an ecological time-series study to correlate the Colombian incidence rate with reductions in mobility trends of retail stores. RESULTS: The meta-analysis of ß coefficients describing the association between case rates and reductions in mobility trends of retail stores resulted in a mean estimate of 0.0637 (95% confidence interval 0.027 to 0.101; p<0.001) with nearly 100% heterogeneity. CONCLUSIONS: We recommend continuing to consider mobility restrictions when the number of cases starts to climb in each local jurisdiction.

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INTRODUCCIÓN: Hasta la fecha, la prevalencia y gravedad de la enfermedad COVID- 19 en niños es menor que en adultos. Existen controversias en relación a la dinámica de la transmisión y al rol que juegan en la diseminación de la enfermedad. OBJETIVO: Describir las características clínicas y la dinámica de transmisión de los pacientes bajo 15 años de edad notificados por sospecha y/o contacto para COVID-19 en el período 13 marzo - 20 noviembre 2020, en un prestador integral privado de salud (Médica Uruguaya Corporación de Asistencia Médica, MUCAM). METODOLOGÍA: Estudio descriptivo, retrospectivo, en el que se describen manifestaciones clínicas, noción epidemiológica, casos secundarios, gravedad y evolución. Se estimó el riesgo y la tasa de ataque secundaria intradomiciliaria. RESULTADOS: Cumplieron los criterios de inclusión 539 pacientes. El diagnóstico se confirmó en 29 (5,3%): 13 (7,0%) de los 351 niños sintomáticos y 16 (4,5%) de los 188 asintomáticos. Tuvieron noción de contacto el 100% de los casos confirmados y 85% de los no confirmados (p < 0.05). El OR para la infección a partir de un contacto intradomiciliario fue 26,5 (9,8- 71,7) y la tasa de ataque secundaria intradomiciliaria 23% ± 4,1. CONCLUSIONES: En esta serie, en los pacientes bajo 15 años de edad predominaron las formas leves y asintomáticas. Uno de cada cinco expuestos intradomiciliarios contrajo la enfermedad siendo esta noción de contacto decisiva para indicar estudios confirmatorios. La mayoría de los niños no continuó la cadena de transmisión.

BACKGROUND: To date, the prevalence and severity of the COVID-19 disease in children is lower than in adults. There are controversies regarding the dynamics of transmission and the role they play in the spread of the disease. AIM: To describe the clinical characteristics and transmission dynamics of patients under 15 years of age reported for suspicion and/or contact for COVID-19 in the period March 13 - November 20, 2020, in a private comprehensive health provider (Médica Uruguaya Medical Assistance Corporation, MUCAM). METHODS: Descriptive, retrospective study, in which clinical manifestations, epidemiological notion, secondary cases, severity and evolution are described. The risk and rate of secondary intradomiciliary attack were estimated. RESULTS: 539 patients met the inclusion criteria. The diagnosis was confirmed in 29 (5.3%): 13 (7.0%) of the 351 symptomatic children and 16 (4.5%) of the 188 asymptomatic. 100% of the confirmed cases and 85% of the unconfirmed cases had the notion of contact (p < 0.05). The OR for infection from an indoor contact was 26.5 (9.8-71.7) and the rate of secondary indoor attack 23% ± 4.1. CONCLUSIONS: In this series, mild and asymptomatic forms predominated in patients under 15 years of age. One in five exposed indoors contracted the disease, this notion of contact being decisive to indicate confirmatory studies. Most of the children did not continue the chain of transmission.

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Abstract INTRODUCTION Severe acute respiratory syndrome coronavirus 2 has been transmitted to more than 200 countries, with 92.5 million cases and 1,981,678 deaths. METHODS This study applied a mathematical model to estimate the increase in the number of cases in São Paulo state, Brazil during four epidemic periods and the subsequent 300 days. We used different types of dynamic transmission models to measure the effects of social distancing interventions, based on local contact patterns. Specifically, we used a model that incorporated multiple transmission pathways and an environmental class that represented the pathogen concentration in the environmental reservoir and also considered the time that an individual may sustain a latent infection before becoming actively infectious. Thus, this model allowed us to show how the individual quarantine and active monitoring of contacts can influence the model parameters and change the rate of exposure of susceptible individuals to those who are infected. RESULTS The estimated basic reproductive number, R o , was 3.59 (95% confidence interval [CI]: 3.48 - 3.72). The mathematical model data prediction coincided with the real data mainly when the social distancing measures were respected. However, a lack of social distancing measures caused a significant increase in the number of infected individuals. Thus, if social distancing measures are not respected, we estimated a difference of at least 100,000 cases over the next 300 days. CONCLUSIONS: Although the predictive capacity of this model was limited by the accuracy of the available data, our results showed that social distancing is currently the best non-pharmacological measure.

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Predicting arbovirus re-emergence remains challenging in regions with limited off-season transmission and intermittent epidemics. Current mathematical models treat the depletion and replenishment of susceptible (non-immune) hosts as the principal drivers of re-emergence, based on established understanding of highly transmissible childhood diseases with frequent epidemics. We extend an analytical approach to determine the number of 'skip' years preceding re-emergence for diseases with continuous seasonal transmission, population growth and under-reporting. Re-emergence times are shown to be highly sensitive to small changes in low R0 (secondary cases produced from a primary infection in a fully susceptible population). We then fit a stochastic Susceptible-Infected-Recovered (SIR) model to observed case data for the emergence of dengue serotype DENV1 in Rio de Janeiro. This aggregated city-level model substantially over-estimates observed re-emergence times either in terms of skips or outbreak probability under forward simulation. The inability of susceptible depletion and replenishment to explain re-emergence under 'well-mixed' conditions at a city-wide scale demonstrates a key limitation of SIR aggregated models, including those applied to other arboviruses. The predictive uncertainty and high skip sensitivity to epidemiological parameters suggest a need to investigate the relevant spatial scales of susceptible depletion and the scaling of microscale transmission dynamics to formulate simpler models that apply at coarse resolutions.

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OBJECTIVE: Establishing a social contact data sharing initiative and an interactive tool to assess mitigation strategies for COVID-19. RESULTS: We organized data sharing of published social contact surveys via online repositories and formatting guidelines. We analyzed this social contact data in terms of weighted social contact matrices, next generation matrices, relative incidence and R[Formula: see text]. We incorporated location-specific physical distancing measures (e.g. school closure or at work) and capture their effect on transmission dynamics. All methods have been implemented in an online application based on R Shiny and applied to COVID-19 with age-specific susceptibility and infectiousness. Using our online tool with the available social contact data, we illustrate that physical distancing could have a considerable impact on reducing transmission for COVID-19. The effect itself depends on assumptions made about disease-specific characteristics and the choice of intervention(s).

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In Costa Rica, the first known cases of Zika were reported in 2016. We looked at the 2016-2017 Zika outbreak and explored the transmission dynamics using weekly reported data. A nonlinear differential equation single-outbreak model with sexual transmission, as well as host availability for vector-feeding was used to estimate key parameters, fit the data and compute the basic reproductive number, R0, distribution. Furthermore, a sensitivity and elasticity analysis was computed based on the R0 parameters.

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BACKGROUND: The parasite Leishmania infantum causes zoonotic visceral leishmaniasis (VL), a potentially fatal vector-borne disease of canids and humans. Zoonotic VL poses a significant risk to public health, with regions of Latin America being particularly afflicted by the disease. Leishmania infantum parasites are transmitted between hosts during blood-feeding by infected female phlebotomine sand flies. With a principal reservoir host of L. infantum being domestic dogs, limiting prevalence in this reservoir may result in a reduced risk of infection for the human population. To this end, a primary focus of research efforts has been to understand disease transmission dynamics among dogs. One way this can be achieved is through the use of mathematical models. METHODS: We have developed a stochastic, spatial, individual-based mechanistic model of L. infantum transmission in domestic dogs. The model framework was applied to a rural Brazilian village setting with parameter values informed by fieldwork and laboratory data. To ensure household and sand fly populations were realistic, we statistically fitted distributions for these entities to existing survey data. To identify the model parameters of highest importance, we performed a stochastic parameter sensitivity analysis of the prevalence of infection among dogs to the model parameters. RESULTS: We computed parametric distributions for the number of humans and animals per household and a non-parametric temporal profile for sand fly abundance. The stochastic parameter sensitivity analysis determined prevalence of L. infantum infection in dogs to be most strongly affected by the sand fly associated parameters and the proportion of immigrant dogs already infected with L. infantum parasites. CONCLUSIONS: Establishing the model parameters with the highest sensitivity of average L. infantum infection prevalence in dogs to their variation helps motivate future data collection efforts focusing on these elements. Moreover, the proposed mechanistic modelling framework provides a foundation that can be expanded to explore spatial patterns of zoonotic VL in humans and to assess spatially targeted interventions.

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Malaria is a deadly disease transmitted to human through the bite of infected female mosquitoes. The aim of this paper is to study the different vector-bias values between low and high transmission areas with the examples of Mexico (low) and Sudan, Democratic Republic of the Congo (Congo, DR) (high) during malaria transmission. We develop a malaria transmission model with vector-bias and investigate the basic reproduction number, the existence of equilibria and the corresponding globally asymptotically stable. Then, we simulate the reported cases of Mexico and Sudan, Democratic Republic of the Congo by World Health Organization (WHO) (WHO, 0000) and predict the direction of the disease. Our simulation results show that the most endemic country is Congo, DR with the highest vector-bias and R0 values, followed by Sudan and Mexico with less, respectively and that the disease will die out in Mexico and persist in Sudan and Congo, DR. Furthermore, we perform sensitivity analysis of R0 and give some useful comments on reducing the cases of the disease.

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OBJECTIVE: To analyse the temporal and spatial distribution as well as the environmental and socioeconomic factors associated with cutaneous leishmaniasis incidence in the state of Amazonas, Brazil from 2007 to 2015. METHODS: Spatial and temporal distribution was evaluated from sequential thematic maps of the mean incidence rates of the disease. A negative binomial regression analysis was performed to evaluate the association of the factors studied with the mean incidence rate of ACL. RESULTS: The average proportion of deforestation was negatively associated with the average incidence rate of cutaneous leishmaniasis in municipalities (ß = -2.178; P = 0.019; 95%CI -3.996, -0.361), and the health system performance index (effectiveness) (ß = -0.852; P = 0.008; 95%CI -1.481, -0.225). Conversely, the municipal human development index (MHDI) was a factor positively related to the average incidence among the municipalities (ß = 7.728; P = 0.003; 95%CI 2.716, 12.738). CONCLUSION: Our study shows the important impact of socioeconomic and environmental factors on ACL incidence in the Amazonas State.

OBJECTIF: Analyser la distribution temporelle et spatiale ainsi que les facteurs environnementaux et socioéconomiques associés à l'incidence de la leishmaniose cutanée dans l'Etat de l'Amazonas, au Brésil, de 2007 à 2015. MÉTHODES: La distribution spatiale et temporelle a été évaluée à partir de cartes thématiques séquentielles des taux d'incidence moyens de la maladie. Une analyse de régression binomiale négative a été réalisée pour évaluer l'association des facteurs étudiés avec le taux d'incidence moyen de la LCA. RÉSULTATS: La proportion moyenne de déforestation était négativement associée au taux d'incidence moyen de la leishmaniose cutanée dans les municipalités (ß = -2,178; p = 0,019; IC95%: -3,996 à -0,361) et à l'indice de performance du système de santé (efficacité) (ß = -0,852; p = 0,008; IC95%: -1,481 à -0,225). Par contre, l'indice de développement humain municipal (IDHM) était un facteur positivement lié à l'incidence moyenne dans les municipalités (ß = 7,728; p = 0,003; IC95%: 2,716 à 12,738). CONCLUSION: Notre étude montre l'impact important des facteurs socioéconomiques et environnementaux sur l'incidence de la LCA dans l'Etat d'Amazonas.

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Leishmaniasis is a neglected tropical disease caused by the Leishmania parasite and transmitted by the Phlebotominae subfamily of sandflies, which infects humans and other mammals. Clinical manifestations of the disease include cutaneous leishmaniasis (CL), mucocutaneous leishmaniasis (MCL) and visceral leishmaniasis (VL) with a majority (more than three-quarters) of worldwide cases being CL. There are a number of risk factors for CL, such as the presence of multiple reservoirs, the movement of individuals, inequality, and social determinants of health. However, studies related to the role of these factors in the dynamics of CL have been limited. In this work, we (i) develop and analyze a vector-borne epidemic model to study the dynamics of CL in two ecologically distinct CL-affected regions-Madrid, Spain and Tolima, Colombia; (ii) derived three different methods for the estimation of model parameters by reducing the dimension of the systems; (iii) estimated reproduction numbers for the 2010 outbreak in Madrid and the 2016 outbreak in Tolima; and (iv) compared the transmission potential of the two economically-different regions and provided different epidemiological metrics that can be derived (and used for evaluating an outbreak), once R0 is known and additional data are available. On average, Spain has reported only a few hundred CL cases annually, but in the course of the outbreak during 2009⁻2012, a much higher number of cases than expected were reported and that too in the single city of Madrid. Cases in humans were accompanied by sharp increase in infections among domestic dogs, the natural reservoir of CL. On the other hand, CL has reemerged in Colombia primarily during the last decade, because of the frequent movement of military personnel to domestic regions from forested areas, where they have increased exposure to vectors. In 2016, Tolima saw an unexpectedly high number of cases leading to two successive outbreaks. On comparing, we estimated reproduction number of the Madrid outbreak to be 3.1 (with range of 2.8⁻3.9), which was much higher than reproduction number estimates of the Tolima first outbreak 1.2 (with range of 1.1⁻1.3), and the estimate for the second outbreak in Tolima of 1.019 (with range of 1.018⁻1.021). This suggests that the epidemic outbreak in Madrid was much more severe than the Tolima outbreak, even though Madrid was economically better-off compared to Tolima. It indicates a potential relationship between urban development and increasing health disparities.

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BACKGROUND: Mathematical models of transmission dynamics are routinely fitted to epidemiological time series, which must inevitably be aggregated at some spatial scale. Weekly case reports of chikungunya have been made available nationally for numerous countries in the Western Hemisphere since late 2013, and numerous models have made use of this data set for forecasting and inferential purposes. Motivated by an abundance of literature suggesting that the transmission of this mosquito-borne pathogen is localized at scales much finer than nationally, we fitted models at three different spatial scales to weekly case reports from Colombia to explore limitations of analyses of nationally aggregated time series data. METHODS: We adapted the recently developed Disease Transmission Kernel (DTK)-Dengue model for modeling chikungunya virus (CHIKV) transmission, given the numerous similarities of these viruses vectored by a common mosquito vector. We fitted versions of this model specified at different spatial scales to weekly case reports aggregated at different spatial scales: (1) single-patch national model fitted to national data; (2) single-patch departmental models fitted to departmental data; and (3) multi-patch departmental models fitted to departmental data, where the multiple patches refer to municipalities within a department. We compared the consistency of simulations from fitted models with empirical data. RESULTS: We found that model consistency with epidemic dynamics improved with increasing spatial granularity of the model. Specifically, the sum of single-patch departmental model fits better captured national-level temporal patterns than did a single-patch national model. Likewise, multi-patch departmental model fits better captured department-level temporal patterns than did single-patch departmental model fits. Furthermore, inferences about municipal-level incidence based on multi-patch departmental models fitted to department-level data were positively correlated with municipal-level data that were withheld from model fitting. CONCLUSIONS: Our model performed better when posed at finer spatial scales, due to better matching between human populations with locally relevant risk. Confronting spatially aggregated models with spatially aggregated data imposes a serious structural constraint on model behavior by averaging over epidemiologically meaningful spatial variation in drivers of transmission, impairing the ability of models to reproduce empirical patterns.

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BACKGROUND: The transmission dynamics of human metapneumovirus (HMPV) in tropical countries remain unclear. Further understanding of the genetic diversity of the virus could aid in HMPV vaccine design and improve our understanding of respiratory virus transmission dynamics in low- and middle-income countries. MATERIALS & METHODS: We examined the evolution of HMPV in Peru through phylogenetic analysis of 61 full genome HMPV sequences collected in three ecologically diverse regions of Peru (Lima, Piura, and Iquitos) during 2008-2012, comprising the largest data set of HMPV whole genomes sequenced from any tropical country to date. RESULTS: We revealed extensive genetic diversity generated by frequent viral introductions, with little evidence of local persistence. While considerable viral traffic between non-Peruvian countries and Peru was observed, HMPV epidemics in Peruvian locales were more frequently epidemiologically linked with other sites within Peru. We showed that Iquitos experienced greater HMPV traffic than the similar sized city of Piura by both Bayesian and maximum likelihood methods. CONCLUSIONS: There is extensive HMPV genetic diversity even within smaller and relatively less connected cities of Peru and this virus is spatially fluid. Greater diversity of HMPV in Iquitos compared to Piura may relate to higher volumes of human movement, including air traffic to this location.

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