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Related Concept Videos

Malaria01:29

Malaria

Malaria pathogenesis in humans reflects a delicate interplay between parasite biology and host response. Clinical illness reflects a host’s immune response to the parasite’s asexual replication cycle, which is often asymptomatic in individuals with partial immunity. From the parasite's perspective, transmission between mosquito and human with minimal host pathology is evolutionarily advantageous. Among the six Plasmodium species infecting humans, P. falciparum and P. vivax dominate in global...
Symbiosis00:58

Symbiosis

Symbiotic relationships are long-term, close interactions between individuals of different species that affect the distribution and abundance of those species. When a relationship is beneficial to both species, this is called mutualism. When the relationship is beneficial to one species but neither beneficial nor harmful to the other species, this is called commensalism. When one organism is harmed to benefit another, the relationship is known as parasitism. These types of relationships often...
Biological Clocks and Seasonal Responses02:45

Biological Clocks and Seasonal Responses

The circadian—or biological—clock is an intrinsic, timekeeping, molecular mechanism that allows plants to coordinate physiological activities over 24-hour cycles called circadian rhythms. Photoperiodism is a collective term for the biological responses of plants to variations in the relative lengths of dark and light periods. The period of light-exposure is called the photoperiod.
Patterns of Fever01:26

Patterns of Fever

Before understanding the types and patterns of fever, it is essential to know its phases.

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A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

A simple method for defining malaria seasonality.

Arantxa Roca-Feltrer1, Joanna R M Armstrong Schellenberg, Lucy Smith

  • 1Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK. arantxa.roca-feltrer@lshtm.ac.uk

Malaria Journal
|December 5, 2009
PubMed
Summary
This summary is machine-generated.

A new definition for malaria seasonality helps identify distinct seasonal patterns. This approach aids in localized malaria control strategies and intervention targeting, improving public health outcomes.

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Area of Science:

  • Epidemiology
  • Public Health
  • Infectious Disease Dynamics

Background:

  • Standardized definitions for malaria seasonality are lacking, leading to varied reporting in scientific literature.
  • Understanding malaria seasonality is crucial for optimizing control strategies and intervention timing in endemic areas.

Purpose of the Study:

  • To present a simple, standardized approach for defining malaria seasonality.
  • To aid in localized policymaking and the targeted implementation of malaria control interventions.

Main Methods:

  • Systematic literature reviews identified studies with monthly malaria data (clinical, hospital admissions, entomological inoculation rates).
  • Defined 'marked seasonality' as ≥75% of cases in ≤6 months; 'concentrated period' as the 6 highest-case months.
  • Conducted sensitivity analyses with various data cut-offs.

Main Results:

  • Data from 13, 18, and 11 sites were analyzed for clinical malaria, hospital admissions, and EIR, respectively.
  • Most sites exhibited year-round transmission with seasonal peaks; a subset met the 'marked seasonality' criteria.
  • Monthly entomological inoculation rates (EIR) showed limited value for detecting seasonal variations, especially at lower transmission intensities.

Conclusions:

  • The proposed definition effectively differentiated between 'marked seasonality' and less seasonal sites.
  • The definition showed limitations in areas with bimodal malaria seasonality.
  • Further research is recommended to assess the definition's applicability using routine health data for intervention targeting.