ArticleMalaria journal2014
Towards seasonal forecasting of malaria in India.
Article in Malaria journal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Impact of climate variability on the transmission risk of malaria in northern Côte d'Ivoire.PloS one · 2018Trial
- Spatio-temporal modelling and prediction of malaria incidence in Mozambique using climatic indicators from 2001 to 2018.Scientific reports · 2025Article
- Hybrid models combining trend and seasonality components with machine learning algorithms provide accurate forecasting of malaria incidence.PLOS global public health · 2025Article
- Influence of future climate scenarios using CMIP 5 data on malaria transmission in India.Malaria journal · 2024Article
- Space-time clusters and co-occurrence of Plasmodium vivax and Plasmodium falciparum malaria in West Bengal, India.Malaria journal · 2024Article
- Abstruse Side of Climate Change, Impact on Malaria: A Systematic Evidence Review Comparing Iran versus Globally.Iranian journal of public health · 2024Review
- Time series analysis of malaria cases to assess the impact of various interventions over the last three decades and forecasting malaria in India towards the 2030 elimination goals.Malaria journal · 2024Article
- Predictors of anaemia in mothers and children in Uttar Pradesh, India.Public health nutrition · 2024Article
- Seasonal Distribution and Trend Analysis of Urban Malaria Prevalence in a Malaria Clinic, South Delhi, India, between 2012 and 2019.The American journal of tropical medicine and hygiene · 2022Article
- Predicting malaria outbreaks from sea surface temperature variability up to 9 months ahead in Limpopo, South Africa, using machine learning.Frontiers in public health · 2022Article
- Understanding the effect of climate change in the distribution and intensity of malaria transmission over India using a dynamical malaria model.International journal of biometeorology · 2021Article
- Modeling an association between malaria cases and climate variables for Keonjhar district of Odisha, India: a Bayesian approach.Journal of parasitic diseases : official organ of the Indian Society for Parasitology · 2020Article
- Malaria predictions based on seasonal climate forecasts in South Africa: A time series distributed lag nonlinear model.Scientific reports · 2019Article
- Shift in Potential Malaria Transmission Areas in India, Using the Fuzzy-Based Climate Suitability Malaria Transmission (FCSMT) Model under Changing Climatic Conditions.International journal of environmental research and public health · 2019Article
- Weather-based forecasting of mosquito-borne disease outbreaks in Canada.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2019Article
- Dynamical Malaria Forecasts Are Skillful at Regional and Local Scales in Uganda up to 4 Months Ahead.GeoHealth · 2019Article
- Identifying climate drivers of infectious disease dynamics: recent advances and challenges ahead.Proceedings. Biological sciences · 2017Review
- Using remote sensing environmental data to forecast malaria incidence at a rural district hospital in Western Kenya.Scientific reports · 2017Article
- Predictability of epidemic malaria under non-stationary conditions with process-based models combining epidemiological updates and climate variability.Malaria journal · 2015Article
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Authors and funding
10 authors.
Funding
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Abstract
backgroundMalaria presents public health challenge despite extensive intervention campaigns. A 30-year hindcast of the climatic suitability for malaria transmission in India is presented, using meteorological variables from a state of the art seasonal forecast model to drive a process-based, dynamic disease model.
methodsThe spatial distribution and seasonal cycles of temperature and precipitation from the forecast model are compared to three observationally-based meteorological datasets. These time series are then used to drive the disease model, producing a simulated forecast of malaria and three synthetic malaria time series that are qualitatively compared to contemporary and pre-intervention malaria estimates. The area under the Relative Operator Characteristic (ROC) curve is calculated as a quantitative metric of forecast skill, comparing the forecast to the meteorologically-driven synthetic malaria time series. RESULTS AND DISCUSSION: The forecast shows probabilistic skill in predicting the spatial distribution of Plasmodium falciparum incidence when compared to the simulated meteorologically-driven malaria time series, particularly where modelled incidence shows high seasonal and interannual variability such as in Orissa, West Bengal, and Jharkhand (North-east India), and Gujarat, Rajastan, Madhya Pradesh and Maharashtra (North-west India). Focusing on these two regions, the malaria forecast is able to distinguish between years of "high", "above average" and "low" malaria incidence in the peak malaria transmission seasons, with more than 70% sensitivity and a statistically significant area under the ROC curve. These results are encouraging given that the three month forecast lead time used is well in excess of the target for early warning systems adopted by the World Health Organization. This approach could form the basis of an operational system to identify the probability of regional malaria epidemics, allowing advanced and targeted allocation of resources for combatting malaria in India.
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