A Review on Major Risk Factors and Current Status of Visceral Leishmaniasis in North India

Singh, N. S.

doi:10.11648/j.aje.20190301.12

Cited by 18 publications

(8 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Visceral leishmaniasis (VL) is the acute disease caused by Leishmania donovani, which is transmitted through infected female Phlebotomus argentipes sandflies. In India, the burden of disease is largely contained within the four northeastern states of Bihar, Jharkhand, Uttar Pradesh and West Bengal, with the rural state of Bihar most broadly affected [1][2][3].…”

Section: Visceral Leishmaniasis In Indiamentioning

confidence: 99%

“…Incidence of VL in India has decreased substantially since the initiation of the regional Kala-Azar Elimination Programme (KEP), which aims to tackle the disease across the Indian subcontinent through enhanced case detection and treatment and reduction of vector density [4]. As a result, reported cases have fallen from 29,000 in 2010 to less than 5,000 in 2018 [3,4]. The overall target of the programme is to reduce incidence to less than 1 case/10,000 people/ year within each "block".…”

Section: Visceral Leishmaniasis In Indiamentioning

confidence: 99%

See 1 more Smart Citation

A spatio-temporal approach to short-term prediction of visceral leishmaniasis diagnoses in India

et al. 2020

View full text Add to dashboard Cite

Background The elimination programme for visceral leishmaniasis (VL) in India has seen great progress, with total cases decreasing by over 80% since 2010 and many blocks now reporting zero cases from year to year. Prompt diagnosis and treatment is critical to continue progress and avoid epidemics in the increasingly susceptible population. Short-term forecasts could be used to highlight anomalies in incidence and support health service logistics. The model which best fits the data is not necessarily most useful for prediction, yet little empirical work has been done to investigate the balance between fit and predictive performance. Methodology/Principal findings We developed statistical models of monthly VL case counts at block level. By evaluating a set of randomly-generated models, we found that fit and one-month-ahead prediction were strongly correlated and that rolling updates to model parameters as data accrued were not crucial for accurate prediction. The final model incorporated auto-regression over four months, spatial correlation between neighbouring blocks, and seasonality. Ninety-four percent of 10-90% prediction intervals from this model captured the observed count during a 24-month test period. Comparison of one-, three-and four-month-ahead predictions from the final model fit demonstrated that a longer time horizon yielded only a small sacrifice in predictive power for the vast majority of blocks. Conclusions/Significance The model developed is informed by routinely-collected surveillance data as it accumulates, and predictions are sufficiently accurate and precise to be useful. Such forecasts could, for example, be used to guide stock requirements for rapid diagnostic tests and drugs. More PLOS NEGLECTED TROPICAL DISEASES

show abstract

Section: Visceral Leishmaniasis In Indiamentioning

confidence: 99%

Section: Visceral Leishmaniasis In Indiamentioning

confidence: 99%

A spatio-temporal approach to short-term prediction of visceral leishmaniasis diagnoses in India

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Visceral leishmaniasis (VL) is the acute disease caused by Leishmania donovani , which is transmitted through infected female Phlebotomus argentipes sandflies. In India, the burden of disease is largely contained within the four northeastern states of Bihar, Jharkhand, Uttar Pradesh and West Bengal, with the rural state of Bihar most broadly affected [1–3].…”

Section: Introductionmentioning

confidence: 99%

A Spatio-temporal Approach to Short-Term Prediction of Visceral Leishmaniasis Diagnoses in India

Nightingale

Chapman

Srikantiah

et al. 2019

Preprint

View full text Add to dashboard Cite

Background: The elimination programme for visceral leishmaniasis (VL) in India has seen great progress, with total cases decreasing by over 80% since 2010 and many blocks now reporting zero cases from year to year. Prompt diagnosis and treatment is critical to continue progress and avoid epidemics in the increasingly susceptible population. Short-term forecasts could be used to highlight anomalies in incidence and support health service logistics. The model which best fits the data is not necessarily most useful for prediction, yet little empirical work has been done to investigate the balance between fit and predictive performance. Principal Findings: We developed statistical models of monthly VL case counts at block level. By evaluating a set of randomly-generated models, we found that fit and one-month-ahead prediction were strongly correlated and that rolling updates to model parameters as data accrued were not crucial for accurate prediction. The final model incorporated auto-regression over four months, spatial correlation between neighbouring blocks,and seasonality. Ninety-four percent of 10-90% prediction intervals from this model captured the observed count during a 24-month test period. Comparison of one-, three- and four-month-ahead predictions from the final model fit demonstrated that a longer time horizon yielded only a small sacrifice in predictive power for the vast majority of blocks. Conclusions: The model developed is informed by routinely-collected surveillance data as it accumulates, and predictions are sufficiently accurate and precise to be useful. Such forecasts could, for example, be used to guide stock requirements for rapid diagnostic tests and drugs. More comprehensive data on factors thought to influence geographic variation in VL burden could be incorporated, and might better explain the heterogeneity between blocks and improve uniformity of predictive performance.Integration of the approach in the management of the VL programme would be an important step to ensuring continued successful control. and processing of the data,predictive power more than three months ahead of current data is crucial to make forecasts which can feasibly be acted upon. Some heterogeneity remains in predictive power across the study region which could potentially be improved using unit-specific data on factors believed to be associated with reported VL incidence (e.g. age distribution, socio-economic status and climate)

show abstract

“…In an MD simulation, the protein complex's compactness and fluctuation are depicted by the radius of gyration 7,40 . This analysis demonstrates the folding and unfolding of polypeptide chains or the various protein conformations 41 . The radius of gyration studies was done for Ld citrate synthase and protein‐ligand complex, i.e., Abemaciclib, Amyral, Bazedoxifene, Imatinib, and Vorapaxar estimated the mass of atoms relative to the center of complex's mass.…”

Section: Resultsmentioning

confidence: 99%

“…7,40 This analysis demonstrates the folding and unfolding of polypeptide chains or the various protein conformations. 41 The radius of gyration studies was done for Ld citrate synthase and protein-ligand complex, i.e., Abemaciclib, Amyral, Bazedoxifene, Imatinib, and Vorapaxar estimated the mass of atoms relative to the center of complex's mass. The radius of the gyration graph was shown in Figure 2D, which showed that most of the complex was more stable than apoprotein.…”

Section: Molecular Dynamic Simulation Analysis Of the Selected Compoundmentioning

confidence: 99%

Novel chemical scaffold as potential drug against Leishmania donovani: Integrated computational and experimental approaches

Ranjan,

Dubey

2023

J of Cellular Biochemistry

View full text Add to dashboard Cite

In this study, we have screened a large number of Food and Drug Administration‐approved compounds for novel anti‐leishmanial molecules targeting the citrate synthase enzyme of the parasite. Based on their docking and molecular dynamic simulation statistics, five compounds were selected. These compounds followed Lipinski's rule of five. Additionally, in vitro, antileishmanial and cytotoxicity studies were performed. The three compounds, Abemaciclib, Bazedoxifene, and Vorapaxar, had shown effective anti‐leishmanial activities with IC50 values of 0.92 ± 0.02, 0.65 ± 0.09, and 6.1 ± 0.91 against Leishmania donovani promastigote and with EC50 values of 1.52 ± 0.37, 2.11 ± 0.38, 10.4 ± 1.27 against intramacrophagic amastigote without significantly harming macrophage cells. Among them, from in silico and antileishmanial activities studies, Abemaciclib had been selected based on their less binding energy, good antileishmanial activities, and also a significant difference in their binding energy with human citrate synthase for cell death mechanistic studies using flow cytometry and a DNA fragmentation assay. The action of this compound resulted in an increased reactive oxygen species production, depolarization of mitochondrial membrane potential, DNA damage, and an increase in the sub‐G1 cell population. These properties are the hallmarks of apoptosis which were further confirmed by apoptotic assay. Based on the above result, this anticancer compound Abemaciclib could be employed as a potential treatment option for leishmaniasis after further confirmation.

show abstract

A Review on Major Risk Factors and Current Status of Visceral Leishmaniasis in North India

Cited by 18 publications

References 45 publications

A spatio-temporal approach to short-term prediction of visceral leishmaniasis diagnoses in India

A spatio-temporal approach to short-term prediction of visceral leishmaniasis diagnoses in India

A Spatio-temporal Approach to Short-Term Prediction of Visceral Leishmaniasis Diagnoses in India

Novel chemical scaffold as potential drug against Leishmania donovani: Integrated computational and experimental approaches

Contact Info

Product

Resources

About