Wind direction and proximity to larval sites determines malaria risk in Kilifi District in Kenya

Midega, Janet; Smith, David L.; Olotu, Ally; Mwangangi, Joseph; Nzovu, Joseph G.; Wambua, Juliana; Nyangweso, George; Mbogo, Charles M.; Christophides, George K.; Marsh, Kevin; Bejon, Philip

doi:10.1038/ncomms1672

Cited by 79 publications

(74 citation statements)

References 41 publications

(57 reference statements)

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“…Important risk factors such as housing type, house proximity to mosquito breeding sites or water drain, toilet facilities, and malaria preventive measures at the household level have been identified in different studies [18][19][20]. Additional factors such as number of bed nets per household, individual's age and residence altitude, and household wealth, peak monthly rainfall can affect malaria prevalence [21,22].…”

Section: Introductionmentioning

confidence: 99%

Prevalence of Malaria and Associated Factors in Dilla Town and the Surrounding Rural Areas, Gedeo Zone, Southern Ethiopia

Ayele¹

2015

J Bacteriol Parasitol

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Although progress in the fight against malaria, about 75% of the land and 60% of the population is exposed to malaria in Ethiopia. The aim of this study was to assess the prevalence and associated factors of malaria in Dilla town and surrounding rural areas, Southern Ethiopia. Institution based, cross sectional study was employed from October 01 to December 29, 2014 in health facilities. A stratified sampling technique was carried out to select representative individuals. A pre-tested structured questionnaire and blood film examination format (n=350) were used as data collection tools. Peripheral blood samples were collected and the presence of malaria parasites was observed microscopically on thick and thin blood smears. Personal data were collected through the householdbased questionnaires. Finally, data were entered and analyzed using SPSS version 20.0. The overall prevalence of malaria in the study area was 16.0% with higher infection rate in the surrounding area (53.6%) and amongst the age group of 15-24 years (35.7%). The predominant Plasmodium species detected was P. vivax (62.5%) followed by P. falciparum (26.8%) and mixed malaria infection of both species (10.7%). Chi-square result revealed that residing in houses with mud block walls and unavailability of insecticide treated bed nets were found to be significantly associated with the risk of getting malaria parasites (p<0.05). Individuals living in nearby stagnant water were found to be two times more likely to get malaria parasites than those who were far away from these risky areas (OR=2.01, 95% CI: 1.50-3.85). Houses that had been sprayed with insecticide in the past 6 months were protected against malaria infection (OR=2.45, 95% CI: 2.20-3.99). In conclusion, the prevalence of malaria reported in the current study was higher than reports in many areas of the country despite its reduction from year to year.

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Section: Introductionmentioning

confidence: 99%

Prevalence of Malaria and Associated Factors in Dilla Town and the Surrounding Rural Areas, Gedeo Zone, Southern Ethiopia

Ayele¹

2015

J Bacteriol Parasitol

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“…Data revealed that the countries microclimate, topography, population densities, cultural practices, etc also contribute towards the spread of the disease (9). These include residence and leisure activities within close proximity to stagnant bodies of water, public exposure to rural lavatories, general neglect for routine check-up or screening, monthly rainfall, etc (10,11,12,13). …”

Section: Introductionmentioning

confidence: 99%

Prevalence of malaria infection among patients attending Murtala Muhammed specialist hospital Kano, Nigeria

Oladele¹,

Onuoha²,

Hamafyelto³

et al. 2019

Af J Clin Exp Micro

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Malaria is one of the most common diseased conditions in Nigeria and across most developing countries triggered by one of four species of Plasmodium. The objective of this study was to screen and detect for the presence of Plasmodium species via microscopic analysis on Malaria patients attending a healthcare facility Northern Nigeria and present the epidemiological data of malaria.Finger prick blood samples, Thick and Thin Giemsa-stained blood smears, were collected from 350 malaria-suspected individuals representing all age groups. The Giemsa-stained blood smears were examined microscopically. Demographic information on rural and urban dwellings, use of insecticides and mosquito nets were collected using structured questionnaires. Malaria cases were detected in in 227 (64.9%) of the participants with a higher infection rate amongst the males (147) than the females (80). The predominant specie found was Plasmodium falciparum. All age groups in this study were vulnerable in the order of 61-above>31-40>51-60>41-50>1-10>21-30> 11-20 years of age.A large number of participants dwelling in urban area (219) were tested positive for malaria in contrast to eight(8) from the rural area. Not using insecticides and mosquito treated nets were significantly associated with the prevalence of malaria as 59.4% of participants who were tested positive for Plasmodium falciparum infection utilized insecticides, while 66.9% of those who did not were also tested positive. Individuals residing close to gutters and bushes were the most susceptible (85.6%) to Plasmodium infection. Keywords: Prevalence, Malaria, Plasmodium falciparum, Kano. PRÉVALENCE DE L'INFECTION PARMI LES PATIENTS FRÉQUENTANT L'HÔPITAL

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“…Wind speed or direction was not systematically measured in this study, but values from 12 to 18 km/hour were usually encountered, as measured visually by the Beaufort scale, and could influence mosquito flight and dispersal. 42,53 Flight dispersal studies were not performed in Side road 19 and it cannot be ascertained if the mosquito will breed in transitional ponds that are over 400 m away from human dwellings due to lack of variance: only one pond in this study site was located at such a distance.…”

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confidence: 99%

“…42 Very focal high-risk areas of malaria transmission in the Peruvian Amazon were mentioned to be in close proximity to secondary forest-covered larval habitats in a riverine community. 43 The association of proximity to the fringe and malaria has been previously mentioned in the Machadinho Colonization Project, in Rondônia State, 44 where it was observed that settlers living at distances > 50 m from the forest had an OR of 0.4043 of being infected with malaria, that is, there was an OR of 2.47 and a 60% increased rise in malaria odds for settlers living closer to the forest fringe.…”

mentioning

confidence: 99%

Deforestation and Malaria on the Amazon Frontier: Larval Clustering of Anopheles darlingi (Diptera: Culicidae) Determines Focal Distribution of Malaria

Barros¹,

Honório²

2015

The American Society of Tropical Medicine and Hygiene

103

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Abstract. We performed bimonthly mosquito larval collections during 1 year, in an agricultural settlement in the Brazilian Amazon, as well as an analysis of malaria incidence in neighboring houses. Water collections located at forest fringes were more commonly positive for Anopheles darlingi larvae and Kulldorff spatial analysis pinpointed significant larval clusters at sites directly beneath forest fringes, which were called larval "hotspots." Remote sensing identified 43 "potential" hotspots. Sampling of these areas revealed an 85.7% positivity rate for A. darlingi larvae. Malaria was correlated with shorter distances to potential hotpots and settlers living within 400 m of potential hotspots had a 2.60 higher risk of malaria. Recently arrived settlers, usually located closer to the tip of the triangularly shaped deforestation imprints of side roads, may be more exposed to malaria due to their proximity to the forest fringe. As deforestation progresses, transmission decreases. However, forest remnants inside deforested areas conferred an increased risk of malaria. We propose a model for explaining frontier malaria in the Amazon: because of adaptation of A. darlingi to the forest fringe ecotone, humans are exposed to an increased transmission risk when in proximity to these areas, especially when small dams are created on naturally running water collections.

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Wind direction and proximity to larval sites determines malaria risk in Kilifi District in Kenya

Cited by 79 publications

References 41 publications

Prevalence of Malaria and Associated Factors in Dilla Town and the Surrounding Rural Areas, Gedeo Zone, Southern Ethiopia

Prevalence of Malaria and Associated Factors in Dilla Town and the Surrounding Rural Areas, Gedeo Zone, Southern Ethiopia

Prevalence of malaria infection among patients attending Murtala Muhammed specialist hospital Kano, Nigeria

Deforestation and Malaria on the Amazon Frontier: Larval Clustering of Anopheles darlingi (Diptera: Culicidae) Determines Focal Distribution of Malaria

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