You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["HealthCareActivity", "InjuryOrPoisoning", "BodySubstance", "IntellectualProduct", "AnatomicalStructure", "SpatialConcept", "Chemical", "Bacterium", "MedicalDevice", "Organization", "BiomedicalOccupationOrDiscipline", "Finding", "BiologicFunction", "Virus", "ResearchActivity", "ClinicalAttribute", "PopulationGroup", "Eukaryote", "BodySystem", "Food", "ProfessionalOrOccupationalGroup"].

Please return the output as a JSON object of the format: {"Virus": ["HIV", ...], "Bacterium": ["MRSA", ...], "AnatomicalStructure": ["Lung", ...], "BodySystem": ["CNS", ...], "BodySubstance": ["Serum", ...], "Finding": ["Headache", ...], "InjuryOrPoisoning": ["Fracture", ...], "BiologicFunction": ["Death", ...], "HealthCareActivity": ["Biopsy", ...], "ResearchActivity": ["Clinical trial", ...], "MedicalDevice": ["Lenses", ...], "SpatialConcept": ["Camps", ...], "BiomedicalOccupationOrDiscipline": ["Forensic medicine", ...], "Organization": ["WHO", ...], "ProfessionalOrOccupationalGroup": ["Provider", ...], "PopulationGroup": ["Swimmers", ...], "Chemical": ["Gold", ...], "Food": ["Rice", ...], "IntellectualProduct": ["RPAM", ...], "ClinicalAttribute": ["Biomarker", ...], "Eukaryote": ["Dogs", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Passive case detection of malaria in Ratanakiri Province (Cambodia) to detect villages at higher risk for malaria Cambodia reduced malaria incidence by more than 75% between 2000 and 2015, a target of the Millennium Development Goal 6. The Cambodian Government aims to eliminate all forms of malaria by 2025. The country's malaria incidence is highly variable at provincial level, but less is known at village level. This study used passive case detection (PCD) data at village level in Ratanakiri Province from 2010 to 2014 to describe incidence trends and identify high-risk areas of malaria to be primarily targeted towards malaria elimination. In 2010, the Cambodian malaria programme created a Malaria Information System (MIS) to capture malaria information at village level through PCD by village malaria workers and health facilities. The MIS data of Ratanakiri Province 2010-2014 were used to calculate annual incidence rates by Plasmodium species at province and commune levels. For estimating the trend at provincial level only villages reporting each year were selected. The communal incidences and the number of cases per village were visualized on a map per Plasmodium species and per year. Analysis of spatial clustering of village malaria cases by Plasmodium species was performed by year. Overall, malaria annual incidence rates per 1000 inhabitants decreased from 86 (2010) to 30 (2014). Falciparum incidence decreased (by 79% in 2014 compared to 2010; CI 95% 76-82%) more rapidly than vivax incidence (by 19% in 2014 compared to 2010; CI 95% 5-32%). There were ten to 16 significant spatial clusters each year. Big clusters tended to extend along the Cambodian-Vietnamese border and along the Sesan River. Three clusters appeared throughout all years (2010-2014): one with 21 villages appeared each year, the second shrunk progressively from 2012 to 2014 and the third was split into two smaller clusters in 2013 and 2014. The decline of malaria burden can be attributed to intensive malaria control activities implemented in the areas: distribution of a long-lasting insecticidal net per person and early diagnosis and prompt treatment. Dihydro-artemisinin piperaquine was the only first-line treatment for all malaria cases. No radical treatment with primaquine was provided for Plasmodium vivax cases, which could explain the slow decrease of P. vivax due to relapses. To achieve malaria elimination by 2025, priority should be given to the control of stable malaria clusters appearing over time.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["malaria"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["Dihydro-artemisinin", "primaquine", "piperaquine"], "ClinicalAttribute": [], "Eukaryote": ["P. vivax", "Plasmodium species", "Falciparum", "Plasmodium vivax", "vivax"], "Finding": ["high-risk areas of", "detect"], "Food": [], "HealthCareActivity": ["reporting", "first-line treatment", "early diagnosis"], "InjuryOrPoisoning": [], "IntellectualProduct": ["Malaria Information System", "programme", "MIS", "Millennium Development Goal 6"], "MedicalDevice": ["insecticidal net"], "Organization": ["Government", "health facilities"], "PopulationGroup": ["person"], "ProfessionalOrOccupationalGroup": ["malaria workers"], "ResearchActivity": ["PCD", "study", "Passive case detection", "passive case detection"], "SpatialConcept": ["villages", "country\u0027s", "areas", "extend", "village"], "Virus": []}