RESUMO
We present and discuss elaborately a case of malaria misdiagnosis in a 27-year-old woman in Chalus, Mazandaran Province, North Iran in 2013. The patient has been complaining of fever, shivering and myalgia for three months. Although she visited two physicians during this time, the problem still remained owing to misdiagnose. Eventually in hospital after a precise examination on her thick and thin blood film, the causative agent of disease was diagnosed as plasmodium vivax. The patient received treatment accordingly and all clinical manifestations were vanished.
RESUMO
We present and discuss elaborately a case of malaria misdiagnosis in a 27-year-old woman in Chalus, Mazandaran Province, North Iran in 2013. The patient has been complaining of fever, shivering and myalgia for three months. Although she visited two physicians during this time, the problem still remained owing to misdiagnose. Eventually in hospital after a precise examination on her thick and thin blood film, the causative agent of disease was diagnosed as plasmodiumvivax. The patient received treatment accordingly and all clinical manifestations were vanished.
RESUMO
OBJECTIVE: To conduct for modeling spatial distribution of malaria transmission in Iran. METHODS: Records of all malaria cases from the period 2008-2010 in Iran were retrieved for malaria control department, MOH&ME. Metrological data including annual rainfall, maximum and minimum temperature, relative humidity, altitude, demographic, districts border shapefiles, and NDVI images received from Iranian Climatologic Research Center. Data arranged in ArcGIS. RESULTS: 99.65% of malaria transmission cases were focused in southeast part of Iran. These transmissions had statistically correlation with altitude (650 m), maximum (30 °C), minimum (20 °C) and average temperature (25.3 °C). Statistical correlation and overall relationship between NDVI (118.81), relative humidity (⩾45%) and rainfall in southeast area was defined and explained in this study. CONCLUSIONS: According to ecological condition and mentioned cut-off points, predictive map was generated using cokriging method.
