Seasonal forecasts of normalized malaria case anomalies for Uganda 1993-2014 - Adrian Mark Tompkins; Felipe J Colón-González; Francesca Di Giuseppe; Didas B Namanya (PANGAEA, 2019)
The dataset consists of two components —– 1. Seasonal forecasts at lead time 1 month and lead time 4 months of temperature and rainfall from the ECMWF extended range EPS and seasonal forecast system 4, and of relevant parameters related to malaria incidence and transmission that are produced by the VECTRI malaria model driven by the forecast data. a) Rain: Monthly averaged rainfall (mm/day) b) Temp: Monthly averaged Two metre temperature (deg C) c) water_frac: The fraction of the gridcell covered by temporary water bodies that can act as breeding sites d) PRd: Parasite Ratio, proportion of people that have detectable infection e) EIR: Entomological Inoculation rate, number of infective bites per person per unit day. f) anneir: EIR converted to annual units g) lneir: log function of EIR as a proxy for clinical cases (see manuscript for details) Global attributes give model version and parameter settings for simulations Data covers period from 1993 to 2014. —– 2. Normalized district case anomalies from Uganda covering oeriod 2004 to 2010, with model forecast data projected to shapefiles for ease of comparison CSV file with the following format: District name, year, lead month, case anomaly, fc anom mem0, mem1, mem2, mem3
Supplement to: Tompkins, AM et al. (2019): Dynamical Malaria Forecasts Are Skillful at Regional and Local Scales in Uganda up to 4 Months Ahead. GeoHealth, 3(3), 58-66, https://doi.org/10.1029/2018GH000157