Evaluation of parasitemia by qPCR in patients with chronic Chagas disease treated with benznidazole

Objective:To evaluate parasitemia by qPCR in patients undergoing etiological treatment and followed in a Brazilian reference center.Methods:Parasite load was quantified by qPCR in 32 participants with chronic Chagas disease who were treated with benznidazole.Serological analyses were performed before and after the treatment and parasite loads were compared prior and 12/18 months post the treatment.Results:Thirty-two participants were recruited and treated with benznidazole,and 20 were followed-up.Adverse events(AE)were observed in 22 out of 29 participants that had safety data(76%),and dermatological alterations were the most frequently observed AE.Of the 20 participants analyzed,13 and 7 completed 12 and 18 months follow-up after the treatment,respectively.12 Months after the final treatment,Trypanosoma cruzi was detectable in 3 patients by qPCR;18 months after the final treatment,Trypanosoma cruzi was detectable per qPCR in 4 of the 7 participants.Thus,between 12 and 18 months,7 participants of the 20 initial follow-up cases showed positive qPCR,indicating treatment failures.Conclusions:qPCR can be used as an alternative method for evaluating the effectiveness of the etiological treatment of CD,and can be applied to analyze early therapeutic failures.The study showed that benznidazole therapy had limited effectiveness in treating chronic CD patients,thus emphasizing the importance of conducting continued research for developing more effective therapies and diagnosis for CD.

Methods and parameters of melting curve analysis for identification of Leishmania species:A scoping review

Leishmaniasis is a set of diseases with a worldwide distribution that affects mainly economically underprivileged populations in developing countries. It has a major impact on public health, with a global cost of billions of dollars per year. The treatment and control of leishmaniasis vary according to the Leishmania species involved, which require reliable methods for species identification. Since most of the currently used methods have limitations, there is a need for assays that allow rapid, precise identification of the offending species. Real-time polymerase chain reactions in conjunction with dissociation curve analysis have been used to detect differences in the DNA composition of selected genes of Leishmania spp. Kinetoplast DNA is the main molecular target used because of its high copy number per parasite, but other targets have also been studied. As part of an effort to establish melting temperature standards for each target gene, we have reviewed the pertinent literature available in public databases, including Pub Med, Web of Science, Sci ELO and LILACS, using the keywords "Leishmania", "leishmaniasis", "realtime PCR", "melting temperature", and "melting curve", alone or in combination. After applying eligibility criteria, 27 articles were selected for analysis. A considerable variation in the methodologies analyzed was found regarding molecular targets, standardization of the methods, reproducibility and specificity. Because of this, statistical analysis was not performed. In most cases, the methods were able to differentiate the parasite at the subgenus level or few species regardless of the target chosen.

Ultrastructural and enzymatic alterations in the ovary of Rhodnius prolixus infected with Trypanosoma rangeli

Objective:To investigate the morphological structure of ovarian follicular cells and biochemical parameters of both ovaries and fat bodies(sites of vitellogenesis)from Rhodnius(R.)prolixus infected with Trypanosoma(T.)rangeli.Methods:Adult virgin females of R.prolixus were fed upon a membrane apparatus containing heat-inactivated citrated rabbit blood and a suspension of T.rangeli epimastigotes(Macias strain).Females from the control group and all the males received parasite-free blood.Transmission electron microscopy was used to reveal the morphological aspects of ovarian follicle cells in both control and parasite-infected groups.Protein profile,proteolytic activities and Western blotting analyses were performed in either ovary or fat body samples of control and parasite-infected groups.Results:According to the ultrastructural data,T.rangeli infection elicited a degeneration process in the ovarian follicular cells of R.prolixus.Proteolytic assays indicated a reduction in the activity of aspartic peptidases in the ovary and fat body from parasite-infected group,while a significant increase in the cysteine peptidase activity was measured in both insect organs.Additionally,immunoblotting revealed that vitellogenin was overexpressed in the ovary of parasite-infected insects.Conclusions:T.rangeli infection seems to elicit an early programmed cell death in the ovarian follicle cells as well as induces the modulation on the activities of different peptidase classes in either ovaries or fat bodies and the overexpression of the vitellogenin in the ovary of R.prolixus.

Big data technology in infectious diseases modeling,simulation,and prediction after the COVID-19 outbreak

After the outbreak of COVID-19,the interaction of infectious disease systems and social systems has challenged traditional infectious disease modeling methods.Starting from the research purpose and data,researchers im-proved the structure and data of the compartment model or used agents and artificial intelligence based models to solve epidemiological problems.In terms of modeling methods,the researchers use compartment subdivi-sion,dynamic parameters,agent-based model methods,and artificial intelligence related methods.In terms of factors studied,the researchers studied 6 categories:human mobility,nonpharmaceutical interventions(NPIs),ages,medical resources,human response,and vaccine.The researchers completed the study of factors through modeling methods to quantitatively analyze the impact of social systems and put forward their suggestions for the future transmission status of infectious diseases and prevention and control strategies.This review started with a research structure of research purpose,factor,data,model,and conclusion.Focusing on the post-COVID-19 infectious disease prediction simulation research,this study summarized various improvement methods and analyzes matching improvements for various specific research purposes.

Epidemiological shift and geographical heterogeneity in the burden of leptospirosis in China

Background:Leptospirosis morbidity and mortality rates in China have decreased since the 2000s.Further analyses of the spatiotemporal and demographic changes occurring in the last decade and its implication on estimates of disease burden are required to inform intervention strategies.In this study,we quantified the epidemiological shift and geographical heterogeneity in the burden of leptospirosis during 2005-2015 in China.Methods:We used reported leptospirosis case data from 1st January 2005 to 31st of December 2015 that routinely collected by the China Information System for Disease Control and Prevention(CISDCP)to analyze the epidemiological trend and estimate the burden in terms of disability-adjusted life-years(DALYs)over space,time,and demographical groups.Results:A total of 7763 cases were reported during 2005-2015.Of which,2403(31%)cases were the laboratoryconfirmed case.Since 2005,the notified incidence rate was gradually decreased(P<0.05)and it was relatively stable during 2011-2015(P>0.05).During 2005-2015,we estimated a total of 10313 DALYs were lost due to leptospirosis comprising a total of 1804 years-lived with disability(YLDs)and 8509 years-life lost(YLLs).Males had the highest burden of disease(7149 DALYs)compared to females(3164 DALYs).The highest burden estimate was attributed to younger individuals aged 10-19 years who lived in southern provinces of China.During 2005-2015,this age group contributed to approximately 3078 DALYs corresponding to 30%of the total DALYs lost in China.Yet,our analysis indicated a declining trend in burden estimates(P<0.001)since 2005 and remained relatively low during 2011-2015.Low burden estimates have been identified in the endemic regions where infections principally distributed.Most of the changes in DALY estimates were driven by changes in YLLs.Conclusions:In the last 11-years,the burden estimates of leptospirosis have shown a declining trend across the country;however,leptospirosis should not be neglected as it remains an important zoonotic disease and potentially affecting the young and productive population in economically less-developed provinces in southern of China.In addition,while in the last five years the incidence has been reported at very low-level,this might not reflect the true incidence of leptospirosis.Strengthened surveillance in the endemic regions is,hence,substantially required to capture the actual prevalence to better control leptospirosis in China.

Discrete time forecasting of epidemics

Forecasting in the domain of infectious diseases aims at estimating the number of cases ahead of time during an epidemic,hence fundamentally requires understanding its dynamics.In fact,estimates about the dynamics help to predict the number of cases in an epidemic,which will depend on determining a few of defining factors such as its starting point,the turning point,growth factor,and the size of the epidemic in total number of cases.In this work a phenomenological model deals with a practical aspect often disregarded in such studies,namely that health surveillance produces counts in batches when aggregated over discrete time,such as days,weeks,months,or other time units.This model enables derivation of equations that permit both estimating key dynamics parameters and forecasting.Results using both severe acute respiratory illness data and synthetic data show that the forecasting follows very well over time the dynamics and is resilient with statistical noise,but has a delay effect due to the discrete time.

Estimating the size of Aedes aegypti populations from dengue incidence data: Implications for the risk of yellow fever outbreaks

In this paper we present a model to estimate the density of aedes mosquitoes in a community affected by dengue.The method consists in fitting a continuous function to the incidence of dengue infections,from which the density of infected mosquitoes is derived straightforwardly.Further derivations allow the calculation of the latent and susceptible mosquitoes'densities,the sum of the three equals the total mosquitoes'density.The method is illustrated with the case of the risk of urban yellow fever resurgence in dengue infested areas but the same procedures apply for other aedes-transmitted infections like Zika and chikungunya viruses.