Description of malaria epidemics and normal transmissions using rainfall variability in Gondar Zuria highland District, Ethiopia
Background: Rainfall is one of the climate variables most studied as it affects malaria occurrence directly. Objective: This study aimed to describe how monthly rainfall variability affects malaria incidence in different years. Methods: A total of 7 years (2013/14–2019/20) retrospective confirmed an...
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| Format: | Article |
| Language: | English |
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Elsevier
2021-08-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844021017564 |
| _version_ | 1819019024612196352 |
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| author | Wossenseged Lemma |
| author_facet | Wossenseged Lemma |
| author_sort | Wossenseged Lemma |
| collection | DOAJ |
| description | Background: Rainfall is one of the climate variables most studied as it affects malaria occurrence directly. Objective: This study aimed to describe how monthly rainfall variability affects malaria incidence in different years. Methods: A total of 7 years (2013/14–2019/20) retrospective confirmed and treated malaria cases in Gondar Zuria district were used for analysis in addition to five (2013/14–2017/18) years retrospective data from Dembia district. Results: The annual rainfalls in the study years showed no statistically significant difference (p = 0. 78). But, variations in rainfalls of the different months (p = 0.000) of the different years were the source of variations for malaria count (incidences) in the different years. Malaria was transmitted throughout the year with the highest peak in November (mean count = 1468.7 ± 697.8) and followed by May (mean count = 1253.4 ± 1391.8), after main Kiremt/Summer and minor Bulg/Spring rains respectively. The lowest transmission was occurred in February (338 ± 240.3) when the rivers were the only source of mosquito vectors. Year 2013/14 (RF = 2351.12 mm) and 2019/20 (RF = 2278.80 mm) with no statistically significant difference (p = 0.977) in annual rainfalls produced 10, 702 (49.2%) and 961 (20%) malaria counts for the Bulg (spring) season respectively due to 581.92 mm (24.8%) higher total Bulg/Spring rain in 2013/14 compared to 124.1 mm (5.45%) in 2019/20. Generally, above normal rainfalls in Bulg/Spring season increased malaria transmission by providing more aquatic habitats supporting the growth of the immature stages. But heavy rains in Summer/Kiremt produced low malaria counts due to the high intensity of the rainfalls which could kill the larvae and pupae. Spearman's correlation analysis indicated that the mean rainfalls of current month (RF) (0 lagged month) (P = 0.025), previous month (RF1) (1 month lagged) (p = 0.000), before previous months (RF2) (2 months lagged) (p = 0.001) and mean RF + RF1 + RF2 (P = 0.001) were positive significantly correlated with mean monthly malaria counts compared to negative significant correlations for temperature variables. Temperature variables negative correlations were interpreted as confounding effects because decreased malaria counts in dry months were due to a decrease in rainfalls. Conclusion: rainfall distribution in different months of a year affects malaria occurrences. |
| first_indexed | 2024-12-21T03:28:44Z |
| format | Article |
| id | doaj.art-e7199c3219ba4aabbe8b685c350489ab |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-12-21T03:28:44Z |
| publishDate | 2021-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-e7199c3219ba4aabbe8b685c350489ab2022-12-21T19:17:31ZengElsevierHeliyon2405-84402021-08-0178e07653Description of malaria epidemics and normal transmissions using rainfall variability in Gondar Zuria highland District, EthiopiaWossenseged Lemma0Corresponding author.; College of Medicine and Health Sciences, School of Biomedical and Laboratory Sciences, Department of Medical Parasitology, University of Gondar, EthiopiaBackground: Rainfall is one of the climate variables most studied as it affects malaria occurrence directly. Objective: This study aimed to describe how monthly rainfall variability affects malaria incidence in different years. Methods: A total of 7 years (2013/14–2019/20) retrospective confirmed and treated malaria cases in Gondar Zuria district were used for analysis in addition to five (2013/14–2017/18) years retrospective data from Dembia district. Results: The annual rainfalls in the study years showed no statistically significant difference (p = 0. 78). But, variations in rainfalls of the different months (p = 0.000) of the different years were the source of variations for malaria count (incidences) in the different years. Malaria was transmitted throughout the year with the highest peak in November (mean count = 1468.7 ± 697.8) and followed by May (mean count = 1253.4 ± 1391.8), after main Kiremt/Summer and minor Bulg/Spring rains respectively. The lowest transmission was occurred in February (338 ± 240.3) when the rivers were the only source of mosquito vectors. Year 2013/14 (RF = 2351.12 mm) and 2019/20 (RF = 2278.80 mm) with no statistically significant difference (p = 0.977) in annual rainfalls produced 10, 702 (49.2%) and 961 (20%) malaria counts for the Bulg (spring) season respectively due to 581.92 mm (24.8%) higher total Bulg/Spring rain in 2013/14 compared to 124.1 mm (5.45%) in 2019/20. Generally, above normal rainfalls in Bulg/Spring season increased malaria transmission by providing more aquatic habitats supporting the growth of the immature stages. But heavy rains in Summer/Kiremt produced low malaria counts due to the high intensity of the rainfalls which could kill the larvae and pupae. Spearman's correlation analysis indicated that the mean rainfalls of current month (RF) (0 lagged month) (P = 0.025), previous month (RF1) (1 month lagged) (p = 0.000), before previous months (RF2) (2 months lagged) (p = 0.001) and mean RF + RF1 + RF2 (P = 0.001) were positive significantly correlated with mean monthly malaria counts compared to negative significant correlations for temperature variables. Temperature variables negative correlations were interpreted as confounding effects because decreased malaria counts in dry months were due to a decrease in rainfalls. Conclusion: rainfall distribution in different months of a year affects malaria occurrences.http://www.sciencedirect.com/science/article/pii/S2405844021017564Highland malariaRainfallTemperatureMalaria incidence (count)Gondar Zuria District |
| spellingShingle | Wossenseged Lemma Description of malaria epidemics and normal transmissions using rainfall variability in Gondar Zuria highland District, Ethiopia Heliyon Highland malaria Rainfall Temperature Malaria incidence (count) Gondar Zuria District |
| title | Description of malaria epidemics and normal transmissions using rainfall variability in Gondar Zuria highland District, Ethiopia |
| title_full | Description of malaria epidemics and normal transmissions using rainfall variability in Gondar Zuria highland District, Ethiopia |
| title_fullStr | Description of malaria epidemics and normal transmissions using rainfall variability in Gondar Zuria highland District, Ethiopia |
| title_full_unstemmed | Description of malaria epidemics and normal transmissions using rainfall variability in Gondar Zuria highland District, Ethiopia |
| title_short | Description of malaria epidemics and normal transmissions using rainfall variability in Gondar Zuria highland District, Ethiopia |
| title_sort | description of malaria epidemics and normal transmissions using rainfall variability in gondar zuria highland district ethiopia |
| topic | Highland malaria Rainfall Temperature Malaria incidence (count) Gondar Zuria District |
| url | http://www.sciencedirect.com/science/article/pii/S2405844021017564 |
| work_keys_str_mv | AT wossensegedlemma descriptionofmalariaepidemicsandnormaltransmissionsusingrainfallvariabilityingondarzuriahighlanddistrictethiopia |