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
A case of malaria infection in a 42-year-old woman in rural area of Mahmodabad, Mazandaran Province, North Iran was reported and discussed elaborately. She was complaining about recurrent fevers, sweating, headache and myalgia in back. After her first admission to hospital due to misdiagnose she did not receive proper treatment and the patient suffered from clinical manifestations again. Eventually in the second admission to another hospital, after a precise examination on her thick and thin blood smear the agent of disease was recognized appropriately as Plasmodium vivax and treated accordingly.
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.