Seroprevalence of Zika in Brazil stratified by age and geographic distribution

Congenital Zika is a devastating consequence of maternal Zika virus infections. Estimates of age-dependent seroprevalence profiles are central to our understanding of the force of Zika virus infections. We set out to calculate the age-dependent seroprevalence of Zika virus infections in Brazil. We analyzed serum samples stratified by age and geographic location, collected from 2016 to 2019, from about 16,000 volunteers enrolled in a Phase 3 dengue vaccine trial led by the Institute Butantan in Brazil. Our results show that Zika seroprevalence has a remarkable age-dependent and geographical distribution, with an average age of the first infection varying from region to region, ranging from 4.97 (3.03–5.41) to 7.24 (6.98–7.90) years. The calculated basic reproduction number, , varied from region to region, ranging from 1.18 (1.04–1.41) to 2.33 (1.54–3.85). Such data are paramount to determine the optimal age to vaccinate against Zika, if and when such a vaccine becomes available.

THE OPTIMUM LEVEL OF MELD TO MINIMIZE THE MORTALITY ON LIVER TRANSPLANTATION WAITING LIST, AND LIVER TRANSPLANTED PATIENT IN SÃO PAULO STATE, BRAZIL

BACKGROUND

After validation in multiple types of liver disease patients, the MELD score was adopted as a standard by which liver transplant candidates with end-stage liver disease were prioritized for organ allocation in the United States since 2002, and in Brazil, since 2006.

AIMS

To analyze the mortality profile of patients on the liver transplant waiting list correlated to MELD score at the moment of transplantation.

METHODS

This study used the data from the Secretary of Health of the São Paulo State, Brazil, which listed 22,522 patients, from 2006 (when MELD score was introduced in Brazil) until June 2009. Patients with acute hepatic failure and tumors were included as well. We also considered the mortality of both non-transplanted and transplanted patients as a function of the MELD score at presentation.

RESULTS

Our model showed that the best MELD score for patients on the liver transplant waiting list associated to better results after liver transplantation was 26.

CONCLUSIONS

We found that the best score for applying to liver transplant waiting list in the State of São Paulo was 26. This is the score that minimizes the mortality in both non-transplanted and liver transplanted patients.

Effects of migration rates and vaccination on the spread of yellow fever in Latin American communities

Objective

To assess how relevant the flow of people between communities is, compared to vaccination and type of vector, on the spread and potential outbreaks of yellow fever in a disease-free host community.

Methods

Using a SEIRV-SEI model for humans and vectors, we applied numerical simulations to the scenarios: (1) migration from an endemic community to a disease-free host community, comparing the performance of Haemagogus janthinomys and Aedes aegypti as vectors; (2) migration through a transit community located on a migratory route, where the disease is endemic, to a disease-free one; and (3) effects of different vaccination rates in the host community, considering the vaccination of migrants upon arrival.

Results

Results show no remarkable differences between scenarios 1 and 2. The type of vector and vaccination coverage in the host community are more relevant for the occurrence of outbreaks than migration rates, with H. janthinomys being more effective than A. aegypti.

Conclusions

With vaccination being more determinant for a potential outbreak than migration rates, vaccinating migrants on arrival may be one of the most effective measures against yellow fever. Furthermore, H. janthinomys is a more competent vector than A. aegypti at similar densities, but the presence of A. aegypti is a warning to maintain vaccination above recommended levels.

Time-dependent vaccine efficacy estimation quantified by a mathematical model

In this paper we calculate the variation of the estimated vaccine efficacy (VE) due to the time-dependent force of infection resulting from the difference between the moment the Clinical Trial (CT) begins and the peak in the outbreak intensity. Using a simple mathematical model we tested the hypothesis that the time difference between the moment the CT begins and the peak in the outbreak intensity determines substantially different values for VE. We exemplify the method with the case of the VE efficacy estimation for one of the vaccines against the new coronavirus SARS-CoV-2.

Prevalence and predictors of anti-SARS-CoV-2 serology in a highly vulnerable population of Rio de Janeiro: A population-based serosurvey

Background

COVID-19 serosurveys allow for the monitoring of the level of SARS-CoV-2 transmission and support data-driven decisions. We estimated the seroprevalence of anti-SARS-CoV-2 antibodies in a large favela complex in Rio de Janeiro, Brazil.

Methods

A population-based panel study was conducted in Complexo de Manguinhos (16 favelas) with a probabilistic sampling of participants aged ≥1 year who were randomly selected from a census of individuals registered in primary health care clinics that serve the area. Participants answered a structured interview and provided blood samples for serology. Multilevel regression models (with random intercepts to account for participants’ favela of residence) were used to assess factors associated with having anti-S IgG antibodies. Secondary analyses estimated seroprevalence using an additional anti-N IgG assay.

Findings

4,033 participants were included (from Sep/2020 to Feb/2021, 22 epidemic weeks), the median age was 39·8 years (IQR:21·8-57·7), 61% were female, 41% were mixed-race (Pardo) and 23% Black. Overall prevalence was 49·0% (95%CI:46·8%-51·2%) which varied across favelas (from 68·3% to 31·4%). Lower prevalence estimates were found when using the anti-N IgG assay. Odds of having anti-S IgG antibodies were highest for young adults, and those reporting larger household size, poor adherence to social distancing and use of public transportation.

Interpretation

We found a significantly higher prevalence of anti-S IgG antibodies than initially anticipated. Disparities in estimates obtained using different serological assays highlight the need for cautious interpretation of serosurveys estimates given the heterogeneity of exposure in communities, loss of immunological biomarkers, serological antigen target, and variant-specific test affinity.

Funding

Fundação Oswaldo Cruz, Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação de Amparo a Pesquisa do Estado do Rio de Janeiro (FAPERJ), the European Union's Horizon 2020 research and innovation programme, Royal Society, Serrapilheira Institute, and FAPESP.

On the role of financial support programs in mitigating the SARS-CoV-2 spread in Brazil

BACKGROUND

During 2020, there were no effective treatments or vaccines against SARS-CoV-2. The most common disease contention measures were social distance (social isolation), the use of face masks and lockdowns. In the beginning, numerous countries have succeeded to control and reduce COVID-19 infections at a high economic cost. Thus, to alleviate such side effects, many countries have implemented socioeconomic programs to fund individuals that lost their jobs and to help endangered businesses to survive.

METHODS

We assess the role of a socioeconomic program, so-called "Auxilio Emergencial" (AE), during 2020 as a measure to mitigate the Coronavirus Disease 2019 (COVID-19) outbreak in Brazil. For each Brazilian State, we estimate the time-dependent reproduction number from daily reports of COVID-19 infections and deaths using a Susceptible-Exposed-Infected-Recovered-like (SEIR-like) model. Then, we analyse the correlations between the reproduction number, the amount of individuals receiving governmental aid, and the index of social isolation based on mobile phone information.

RESULTS

We observed significant positive correlation values between the average values by the AE and median values of an index accounting for individual mobility. We also observed significantly negative correlation values between the reproduction number and this index on individual mobility. Using the simulations of a susceptible-exposed-infected-removed-like model, if the AE was not operational during the first wave of COVID-19 infections, the accumulated number of infections and deaths could be 6.5 (90% CI: 1.3-21) and 7.9 (90% CI: 1.5-23) times higher, respectively, in comparison with the actual implementation of AE.

CONCLUSIONS

Our results suggest that the AE implemented in Brazil had a significant influence on social isolation by allowing those in need to stay at home, which would reduce the expected numbers of infections and deaths.

Nowcasting and forecasting COVID-19 waves: the recursive and stochastic nature of transmission

We propose a parsimonious, yet effective, susceptible-exposed-infected-removed-type model that incorporates the time change in the transmission and death rates. The model is calibrated by Tikhonov-type regularization from official reports from New York City (NYC), Chicago, the State of São Paulo, in Brazil and British Columbia, in Canada. To forecast, we propose different ways to extend the transmission parameter, considering its estimated values. The forecast accuracy is then evaluated using real data from the above referred places. All the techniques accurately provided forecast scenarios for periods 15 days long. One of the models effectively predicted the magnitude of the four waves of infections in NYC, including the one caused by the Omicron variant for periods of 45 days using out-of-sample data.

Reaching the malaria elimination goal in Brazil: a spatial analysis and time-series study

Background

Since 2015, the Global Technical Strategy (GTS) for Malaria 2016–2030 has been adopted by the World Health Organization (WHO) as a comprehensive framework to accelerate progress for malaria elimination in endemic countries. This strategy sets the target of reducing global malaria incidence and mortality rates by 90% in 2030. Here it is sought to evaluate Brazil’s achievements towards reaching the WHO GTS milestone in 2030. Considering the total number of new malaria cases in 2015, the main research question is: will Brazil reach the malaria elimination goal in 2030?

Methods

Analytical strategies were undertaken using the SIVEP-malaria official databases of the Brazilian Malaria Control Programme for the Brazilian Amazon region from 2009 to 2020. Spatial and time-series analyses were applied for identifying municipalities that support the highest numbers of malaria cases over the years. Forecast analysis was used for predicting the estimated number of new cases in Brazil in 2025–2050.

Results

Brazil has significantly reduced the number of new malaria cases in 2020 in comparison with 2015 in the states of Acre (− 56%), Amapá (− 75%), and Amazonas (− 21%); however, they increased in the states of Pará (156%), Rondônia (74%), and Roraima (362%). Forecast of the predicted number of new malaria cases in 2030 is 74,764 (95% CI: 41,116–141,160) in the Brazilian Amazon.

Conclusions

It is likely that Brazil will reduce the number of new malaria cases in the Brazilian Amazon in 2030 in relation to that in 2015. Herein forecast shows a reduction by 46% (74,754 in 2030 forecast/137,982 in 2015), but this reduction is yet far from the proposed reduction under the WHO GTS 2030 milestone (90%). Stable and unbeatable transmission in the Juruá River Valley, Manaus, and Lábrea still support endemic malaria in the Brazilian Amazon. Today’s cross-border malaria is impacting the state of Roraima unprecedently. If this situation is maintained, the malaria elimination goal (zero cases) may not be reached before 2050. An enhanced political commitment is vital to ensure optimal public health intervention designs in the post-2030 milestones for malaria elimination.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-022-00945-5.

Vector control strategies in Brazil: a qualitative investigation into community knowledge, attitudes and perceptions following the 2015-2016 Zika virus epidemic

OBJECTIVE

The World Health Organization declared a Public Health Emergency of International Concern following the rapid emergence of neonatal microcephaly in Brazil during the 2015-2016 Zika virus (ZIKV) epidemic. In response, a national campaign sought to control Aedes mosquito populations and reduce ZIKV transmission. Achieving adherence to vector control or mosquito-bite reduction behaviours, including the use of topical mosquito repellents, is challenging. Coproduction of research at the community level is needed to understand and mitigate social determinants of lower engagement with Aedes preventive measures, particularly within disempowered groups.

DESIGN

In 2017, the Zika Preparedness Latin America Network (ZikaPLAN) conducted a qualitative study to understand individual and community level experiences of ZIKV and other mosquito-borne disease outbreaks. Presented here is a thematic analysis of 33 transcripts from community focus groups and semistructured interviews, applying the Health Belief Model (HBM) to elaborate knowledge, attitudes and perceptions of ZIKV and vector control strategies.

PARTICIPANTS

120 purposively sampled adults of approximate reproductive age (18-45); 103 women participated in focus groups and 17 men in semistructured interviews.

SETTING

Two sociopolitically and epidemiologically distinct cities in Brazil: Jundiaí (57 km north of São Paolo) and Salvador (Bahia state capital).

RESULTS

Four key and 12 major themes emerged from the analysis: (1) knowledge and cues to action; (2) attitudes and normative beliefs (perceived threat, barriers, benefits and self-efficacy); (3) behaviour change (household prevention and community participation); and (4) community preferences for novel repellent tools, vector control strategies and ZIKV messaging.

CONCLUSIONS

Common barriers to repellent adherence were accessibility, appearance and effectiveness. A strong case is made for the transferability of the HBM to inform epidemic preparedness for mosquito-borne disease outbreaks at the community level. Nationally, a health campaign targeting men is recommended, in addition to local mobilisation of funding to strengthen surveillance, risk communication and community engagement.

COVID-19 underreporting and its impact on vaccination strategies

BACKGROUND

Underreporting cases of infectious diseases poses a major challenge in the analysis of their epidemiological characteristics and dynamical aspects. Without accurate numerical estimates it is difficult to precisely quantify the proportions of severe and critical cases, as well as the mortality rate. Such estimates can be provided for instance by testing the presence of the virus. However, during an ongoing epidemic, such tests' implementation is a daunting task. This work addresses this issue by presenting a methodology to estimate underreported infections based on approximations of the stable rates of hospitalization and death.

METHODS

We present a novel methodology for the stable rate estimation of hospitalization and death related to the Corona Virus Disease 2019 (COVID-19) using publicly available reports from various distinct communities. These rates are then used to estimate underreported infections on the corresponding areas by making use of reported daily hospitalizations and deaths. The impact of underreporting infections on vaccination strategies is estimated under different disease-transmission scenarios using a Susceptible-Exposed-Infective-Removed-like (SEIR) epidemiological model.

RESULTS

For the considered locations, during the period of study, the estimations suggest that the number of infected individuals could reach 30% of the population of these places, representing, in some cases, more than six times the observed numbers. These results are in close agreement with estimates from independent seroprevalence studies, thus providing a strong validation of the proposed methodology. Moreover, the presence of large numbers of underreported infections can reduce the perceived impact of vaccination strategies in reducing rates of mortality and hospitalization.

CONCLUSIONS

pBy using the proposed methodology and employing a judiciously chosen data analysis implementation, we estimate COVID-19 underreporting from publicly available data. This leads to a powerful way of quantifying underreporting impact on the efficacy of vaccination strategies. As a byproduct, we evaluate the impact of underreporting in the designing of vaccination strategies.

The legacy of ZikaPLAN: a transnational research consortium addressing Zika

Global health research partnerships with institutions from high-income countries and low- and middle-income countries are one of the European Commission's flagship programmes. Here, we report on the ZikaPLAN research consortium funded by the European Commission with the primary goal of addressing the urgent knowledge gaps related to the Zika epidemic and the secondary goal of building up research capacity and establishing a Latin American-European research network for emerging vector-borne diseases. Five years of collaborative research effort have led to a better understanding of the full clinical spectrum of congenital Zika syndrome in children and the neurological complications of Zika virus infections in adults and helped explore the origins and trajectory of Zika virus transmission. Individual-level data from ZikaPLAN`s cohort studies were shared for joint analyses as part of the Zika Brazilian Cohorts Consortium, the European Commission-funded Zika Cohorts Vertical Transmission Study Group, and the World Health Organization-led Zika Virus Individual Participant Data Consortium. Furthermore, the legacy of ZikaPLAN includes new tools for birth defect surveillance and a Latin American birth defect surveillance network, an enhanced Guillain-Barre Syndrome research collaboration, a de-centralized evaluation platform for diagnostic assays, a global vector control hub, and the REDe network with freely available training resources to enhance global research capacity in vector-borne diseases.

The impact of COVID-19 vaccination delay: A data-driven modeling analysis for Chicago and New York City

Background

By the beginning of December 2020, some vaccines against COVID-19 already presented efficacy and security, which qualify them to be used in mass vaccination campaigns. Thus, setting up strategies of vaccination became crucial to control the COVID-19 pandemic.

Methods

We use daily COVID-19 reports from Chicago and New York City (NYC) from 01-Mar2020 to 28-Nov-2020 to estimate the parameters of an SEIR-like epidemiological model that accounts for different severity levels. To achieve data adherent predictions, we let the model parameters to be time-dependent. The model is used to forecast different vaccination scenarios, where the campaign starts at different dates, from 01-Oct-2020 to 01-Apr-2021. To generate realistic scenarios, disease control strategies are implemented whenever the number of predicted daily hospitalizations reaches a preset threshold.

Results

The model reproduces the empirical data with remarkable accuracy. Delaying the vaccination severely affects the mortality, hospitalization, and recovery projections. In Chicago, the disease spread was under control, reducing the mortality increment as the start of the vaccination was postponed. In NYC, the number of cases was increasing, thus, the estimated model predicted a much larger impact, despite the implementation of contention measures.

The earlier the vaccination campaign begins, the larger is its potential impact in reducing the COVID-19 cases, as well as in the hospitalizations and deaths. Moreover, the rate at which cases, hospitalizations and deaths increase with the delay in the vaccination beginning strongly depends on the shape of the incidence of infection in each city.

Modelling the impact of delaying vaccination against SARS-CoV-2 assuming unlimited vaccine supply

Background

At the moment we have more than 177 million cases and 3.8 million deaths (as of June 2021) around the world and vaccination represents the only hope to control the pandemic. Imperfections in planning vaccine acquisition and difficulties in implementing distribution among the population, however, have hampered the control of the virus so far.

Methods

We propose a new mathematical model to estimate the impact of vaccination delay against the 2019 coronavirus disease (COVID-19) on the number of cases and deaths due to the disease in Brazil. We apply the model to Brazil as a whole and to the State of Sao Paulo, the most affected by COVID-19 in Brazil. We simulated the model for the populations of the State of Sao Paulo and Brazil as a whole, varying the scenarios related to vaccine efficacy and compliance from the populations.

Results

The model projects that, in the absence of vaccination, almost 170 thousand deaths and more than 350 thousand deaths will occur by the end of 2021 for Sao Paulo and Brazil, respectively. If in contrast, Sao Paulo and Brazil had enough vaccine supply and so started a vaccination campaign in January with the maximum vaccination rate, compliance and efficacy, they could have averted more than 112 thousand deaths and 127 thousand deaths, respectively. In addition, for each month of delay the number of deaths increases monotonically in a logarithmic fashion, for both the State of Sao Paulo and Brazil as a whole.

Conclusions

Our model shows that the current delay in the vaccination schedules that is observed in many countries has serious consequences in terms of mortality by the disease and should serve as an alert to health authorities to speed the process up such that the highest number of people to be immunized is reached in the shortest period of time.

Public health messages on arboviruses transmitted by Aedes aegypti in Brazil

BACKGROUND

The outbreak of Zika virus in Brazil in 2015 followed the arrival of chikungunya in 2014 and a long history of dengue circulation. Vital to the response to these outbreaks of mosquito-borne pathogens has been the dissemination of public health messages, including those promoted through risk communication posters. This study explores the content of a sample of posters circulated in Brazil towards the end of the Zika epidemic in 2017 and analyses their potential effectiveness in inducing behaviour change.

METHODS

A content analysis was performed on 37 posters produced in Brazil to address outbreaks of mosquito-borne pathogens. The six variables of the Health Belief Model were used to assess the potential effectiveness of the posters to induce behaviour change.

RESULTS

Three overarching key messages emerged from the posters. These included (i) the arboviruses and their outcomes, (ii) a battle against the mosquito, and (iii) a responsibility to protect and prevent. Among the six variables utilised through the Health Belief Model, cues to action were most commonly featured, whilst the perceived benefits of engaging in behaviours to prevent arbovirus transmission were the least commonly featured.

CONCLUSIONS

The posters largely focused on mosquito-borne transmission and the need to eliminate breeding sites, and neglected the risk of the sexual and congenital transmission of Zika and the importance of alternative preventive actions. This, we argue, may have limited the potential effectiveness of these posters to induce behaviour change.

Vector role and human biting activity of Anophelinae mosquitoes in different landscapes in the Brazilian Amazon

BACKGROUND

Environmental disturbance, deforestation and socioeconomic factors all affect malaria incidence in tropical and subtropical endemic areas. Deforestation is the major driver of habitat loss and fragmentation, which frequently leads to shifts in the composition, abundance and spatial distribution of vector species. The goals of the present study were to: (i) identify anophelines found naturally infected with Plasmodium; (ii) measure the effects of landscape on the number of Nyssorhynchus darlingi, presence of Plasmodium-infected Anophelinae, human biting rate (HBR) and malaria cases; and (iii) determine the frequency and peak biting time of Plasmodium-infected mosquitoes and Ny. darlingi.

METHODS

Anopheline mosquitoes were collected in peridomestic and forest edge habitats in seven municipalities in four Amazon Brazilian states. Females were identified to species and tested for Plasmodium by real-time PCR. Negative binomial regression was used to measure any association between deforestation and number of Ny. darlingi, number of Plasmodium-infected Anophelinae, HBR and malaria. Peak biting time of Ny. darlingi and Plasmodium-infected Anophelinae were determined in the 12-h collections. Binomial logistic regression measured the association between presence of Plasmodium-infected Anophelinae and landscape metrics and malaria cases.

RESULTS

Ninety-one females of Ny. darlingi, Ny. rangeli, Ny. benarrochi B and Ny. konderi B were found to be infected with Plasmodium. Analysis showed that the number of malaria cases and the number of Plasmodium-infected Anophelinae were more prevalent in sites with higher edge density and intermediate forest cover (30-70%). The distance of the drainage network to a dwelling was inversely correlated to malaria risk. The peak biting time of Plasmodium-infected Anophelinae was 00:00-03:00 h. The presence of Plasmodium-infected mosquitoes was higher in landscapes with > 13 malaria cases.

CONCLUSIONS

Nyssorhynchus darlingi, Ny. rangeli, Ny. benarrochi B and Ny. konderi B can be involved in malaria transmission in rural settlements. The highest fraction of Plasmodium-infected Anophelinae was caught from midnight to 03:00 h. In some Amazonian localities, the highest exposure to infectious bites occurs when residents are sleeping, but transmission can occur throughout the night. Forest fragmentation favors increases in both malaria and the occurrence of Plasmodium-infected mosquitoes in peridomestic habitat. The use of insecticide-impregnated mosquito nets can decrease human exposure to infectious Anophelinae and malaria transmission.

Estimating the effects of reopening of schools on the course of the epidemic of COVID-19

In this paper, we present a method to estimate the risk of reopening of schools illustrated with the case of the State of São Paulo, Brazil. The model showed that, although no death of children would result from the reopening of the schools in the three cities analysed, the risk of asymptomatic and symptomatic cases and secondary cases among teachers, school staff and relatives of the children is not negligible. Although the epidemic hit different regions with different intensities, our model shows that, for regions where the incidence profile is similar to the cities analysed, the risk of reopening of schools is still too high. This in spite of the fact that incidences in these cities were declining in the period of the time considered. Therefore, although we cannot extend the result to the entire country, the overall conclusion is valid for regions with a declining incidence and it is even more valid for regions where incidence is increasing. We assumed a very conservative level of infection transmissibility of children of just 10% as that of adults. In spite of the very low level of transmissibility is assumed, the number of secondary cases caused by infected children among teachers, school staff and relatives varied from 2 to 85. It is, therefore, too soon to have any degree of confidence that reopening of schools before the advent of a vaccine is the right decision to take. The purpose of our model and simulations is to provide a method to estimate the risk of school reopening, although we are sure it could be applied as a guide to public health strategies.

Estimating the effects of reopening of schools on the course of the epidemic of COVID-19

In this paper, we present a method to estimate the risk of reopening of schools illustrated with the case of the State of São Paulo, Brazil. The model showed that, although no death of children would result from the reopening of the schools in the three cities analysed, the risk of asymptomatic and symptomatic cases and secondary cases among teachers, school staff and relatives of the children is not negligible. Although the epidemic hit different regions with different intensities, our model shows that, for regions where the incidence profile is similar to the cities analysed, the risk of reopening of schools is still too high. This in spite of the fact that incidences in these cities were declining in the period of the time considered. Therefore, although we cannot extend the result to the entire country, the overall conclusion is valid for regions with a declining incidence and it is even more valid for regions where incidence is increasing. We assumed a very conservative level of infection transmissibility of children of just 10% as that of adults. In spite of the very low level of transmissibility is assumed, the number of secondary cases caused by infected children among teachers, school staff and relatives varied from 2 to 85. It is, therefore, too soon to have any degree of confidence that reopening of schools before the advent of a vaccine is the right decision to take. The purpose of our model and simulations is to provide a method to estimate the risk of school reopening, although we are sure it could be applied as a guide to public health strategies.

Malaria transmission in landscapes with varying deforestation levels and timelines in the Amazon: a longitudinal spatiotemporal study

The relationship between deforestation and malaria is a spatiotemporal process of variation in Plasmodium incidence in human-dominated Amazonian rural environments. The present study aimed to assess the underlying mechanisms of malarial exposure risk at a fine scale in 5-km2 sites across the Brazilian Amazon, using field-collected data with a longitudinal spatiotemporally structured approach. Anopheline mosquitoes were sampled from 80 sites to investigate the Plasmodium infection rate in mosquito communities and to estimate the malaria exposure risk in rural landscapes. The remaining amount of forest cover (accumulated deforestation) and the deforestation timeline were estimated in each site to represent the main parameters of both the frontier malaria hypothesis and an alternate scenario, the deforestation-malaria hypothesis, proposed herein. The maximum frequency of pathogenic sites occurred at the intermediate forest cover level (50% of accumulated deforestation) at two temporal deforestation peaks, e.g., 10 and 35 years after the beginning of the organization of a settlement. The incidence density of infected anophelines in sites where the original forest cover decreased by more than 50% in the first 25 years of settlement development was at least twice as high as the incidence density calculated for the other sites studied (adjusted incidence density ratio = 2.25; 95% CI, 1.38-3.68; p = 0.001). The results of this study support the frontier malaria as a unifying hypothesis for explaining malaria emergence and for designing specific control interventions in the Brazilian Amazon.

Modelling the impact of contact tracing of symptomatic individuals on the COVID-19 epidemic

OBJECTIVES

With the declining numbers of coronavirus disease 2019 (COVID-19) cases in the state of São Paulo, Brazil, social distancing measures have gradually been lifted. However, the risk of a surge in the number of cases cannot be overlooked. Even with the adoption of nonpharmaceutical interventions, such as restrictions on mass gatherings, wearing of masks, and complete or partial closure of schools, other public health measures may help control the epidemic. We aimed to evaluate the impact of the contact tracing of symptomatic individuals on the COVID-19 epidemic regardless of the use of diagnostic testing.

METHODS

We developed a mathematical model that includes isolation of symptomatic individuals and tracing of contacts to assess the effects of the contact tracing of symptomatic individuals on the COVID-19 epidemic in the state of São Paulo.

RESULTS

For a selection efficacy (proportion of isolated contacts who are infected) of 80%, cases and deaths may be reduced by 80% after 60 days when 5000 symptomatic individuals are isolated per day, each of them together with 10 contacts. On the other hand, for a selection efficacy of 20%, the number of cases and deaths may be reduced by approximately 40% and 50%, respectively, compared with the scenario in which no contact-tracing strategy is implemented.

CONCLUSION

Contact tracing of symptomatic individuals may potentially be an alternative strategy when the number of diagnostic tests available is not sufficient for massive testing.

Post-mortem CT vs necropsy in feline medicine

OBJECTIVES

The aim of this study was to compare post-mortem CT findings with necropsy findings in domestic cats.

METHODS

Post-mortem CT and necropsies were performed in 20 cadavers of domestic cats. The sensitivity, specificity and agreement between the post-mortem CT and necropsy findings were determined.

RESULTS

There were a total of 315 post-mortem findings; 183 were identified by post-mortem CT and 132 were identified by necropsy. Post-mortem CT demonstrated a higher sensitivity to identify the findings mainly in bones. The higher indices of agreement between post-mortem CT and necropsy were related to abnormalities of pleural space, bones and joints.

CONCLUSIONS AND RELEVANCE

This study demonstrated that post-mortem CT and necropsy provided different information. Thus, their use in conjunction with each other might improve the understanding of the cause of death and the identification of post-mortem lesions.

The risk of malaria infection for travelers visiting the Brazilian Amazonian region: A mathematical modeling approach

BACKGROUND

Human mobility between malaria endemic and malaria-free areas can hinder control and elimination efforts in the Amazon basin, maintaining Plasmodium circulation and introduction to new areas.

METHODS

The analysis begins by estimating the incidence of malaria in areas of interest. Then, the risk of infection as a function of the duration of stay after t₀ was calculated as the number of infected travelers over the number of arrived travelers. Differential equations were employed to estimate the risk of nonimmune travelers acquiring malaria in Amazonian municipalities. Risk was calculated as a result of the force of the infection in terms of local dynamics per time of arrival and duration of visit.

RESULTS

Maximum risk occurred at the peak or at the end of the rainy season and it was nonlinearly (exponentially) correlated with the fraction of infected mosquitoes. Relationship between the risk of malaria and duration of visit was linear and positively correlated. Relationship between the risk of malaria and the time of arrival in the municipality was dependent on local effects of seasonality.

CONCLUSIONS

The risk of nonimmune travelers acquiring malaria is not negligible and can maintain regional circulation of parasites, propagating introductions in areas where malaria has been eliminated.

The optimal age of vaccination against dengue in Brazil based on serotype-specific forces of infection derived from serological data

In this paper, we study a single serotype transmission model of dengue to determine the optimal vaccination age for Dengvaxia. The transmission dynamics are modelled with an age-dependent force of infection. The force of infection for each serotype is derived from the serological profile of dengue in Brazil without serotype distinction and from serotype-specific reported cases. The risk due to an infection is measured by the probability of requiring hospitalization based on Brazilian Ministry of Health data. The optimal vaccination age is determined for any number and combination of the four distinct dengue virus serotypes DENv1-4. The lifetime expected risk is adapted to include antibody dependent enhancement (ADE) and permanent cross-immunity after two heterologous infections. The risk is assumed to be serostatus-dependent. The optimal vaccination age is computed for constant, serostatus-specific vaccine efficacies. Additionally, the vaccination age is restricted to conform to the licence of Dengvaxia in Brazil and the achievable and minimal lifetime expected risks are compared. The optimal vaccination age obtained for the risk of hospitalization varies significantly with the assumptions relating to ADE and cross-immunity. Risk-free primary infections lead to higher optimal vaccination ages, as do asymptomatic third and fourth infections. Sometimes vaccination is not recommended at all, e.g. for any endemic area with a single serotype if primary infections are risk-free. Restricting the vaccination age to Dengvaxia licensed ages mostly leads to only a slightly higher lifetime expected risk and the vaccine should be administered as close as possible to the optimal vaccination age.

Modelling the effect of a dengue vaccine on reducing the evolution of resistance against antibiotic due to misuse in dengue cases

Background

This paper intends to check whether and how a hypothetical dengue vaccine could contribute to issue of evolution of bacteria resistance against antibiotics by reducing the number of patients that would inappropriately being treated with antibiotics.

Methods

We use a new mathematical model that combines, in a novel way, two previously published papers, one on the evolution of resistance against antibiotics and one classical Ross-Macdonald model for dengue transmission.

Results

The model is simulated numerically and reproduces a real case of evolution of resistance against antibiotics. In addition the model shows that the use of a hypothetical dengue vaccine could help to curb the evolution of resistance against an antibiotic inappropriately used in dengue patients. Both the increase in the proportion of resistant bacteria due to the misuse of antibiotics in dengue cases as a function of the fraction of treated patients and the reduction of that proportion as a function of vaccination coverage occur in a highly non-linear fashion.

Conclusion

The use of a dengue vaccine is helpful in reducing the rate of evolution of antibiotic resistance in a scenario of misuse of the antibiotics in dengue patients.