Multiplex serology demonstrate cumulative prevalence and spatial distribution of malaria in Ethiopia

Assefa, Ashenafi; Ahmed, Ahmed Ali; Deressa, Wakgari; Sime, Heven; Mohammed, Hussein; Kebede, Amha; Solomon, Hiwot; Teka, Hiwot; Gurrala, Kevin; Matei, Brian; Wakeman, Brian S.; Wilson, G. Glenn; Sinha, Ipsita; Maude, Richard J.; Ashton, Ruth A.; Cook, Jackie; Shi, Ya Ping; Drakeley, Chris; Seidlein, Lorenz von; Rogier, Eric; Hwang, Jimee

doi:10.1186/s12936-019-2874-z

Cited by 26 publications

(41 citation statements)

References 32 publications

(45 reference statements)

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“…More than 60% of the nPCR positive cases were identified from Benishangul-Gumuz Region, which is one of the higher malaria transmission region in Ethiopia [5]. The region showed a similar high prevalence of malaria by microscopy and RDTs in this study and in a separate serology study of the same samples [21].…”

Section: Discussionsupporting

confidence: 64%

“…From the EMIS-2015 results, rapid diagnostic test (RDT) prevalence ranged from 10.4% in Benishangul-Gumuz, 1.9% in Tigray, to 1.1% in Amhara. A separate study [21] also found this geographical area to represent a range of malaria transmission from very low to moderate based on seroprevalence. Participants tested by malaria microscopy and RDT that provided DBS samples were selected from the EMIS 2015 samples repository at the Ethiopian Public Health Institute (EPHI) in Addis Ababa, Ethiopia.…”

Section: Study Areamentioning

confidence: 87%

“…Serology methods and results for these samples have been previously reported [21]. Briefly, DBS elutions were assayed using bead-based multiplex assays for IgG antibodies for six.…”

Section: Plasmodium Infection Exposurementioning

confidence: 99%

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Assessment of subpatent Plasmodium infection in northwestern Ethiopia

Assefa

Ahmed

Deressa

et al. 2020

Malar J

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Background: Ethiopia has set a goal for malaria elimination by 2030. Low parasite density infections may go undetected by conventional diagnostic methods (microscopy and rapid diagnostic tests) and their contribution to malaria transmission varies by transmission settings. This study quantified the burden of subpatent infections from samples collected from three regions of northwest Ethiopia.Methods: Sub-samples of dried blood spots from the Ethiopian Malaria Indicator Survey 2015 (EMIS-2015) were tested and compared using microscopy, rapid diagnostic tests (RDTs), and nested polymerase chain reaction (nPCR) to determine the prevalence of subpatent infection. Paired seroprevalence results previously reported along with gender, age, and elevation of residence were explored as risk factors for Plasmodium infection. Results:Of the 2608 samples collected, the highest positive rate for Plasmodium infection was found with nPCR 3.3% (95% CI 2.7-4.1) compared with RDT 2.8% (95% CI 2.2-3.5) and microscopy 1.2% (95% CI 0.8-1.7). Of the nPCR positive cases, Plasmodium falciparum accounted for 3.1% (95% CI 2.5-3.8), Plasmodium vivax 0.4% (95% CI 0.2-0.7), mixed P. falciparum and P. vivax 0.1% (95% CI 0.0-0.4), and mixed P. falciparum and Plasmodium malariae 0.1% (95% CI 0.0-0.3). nPCR detected an additional 30 samples that had not been detected by conventional methods. The majority of the nPCR positive cases (61% (53/87)) were from the Benishangul-Gumuz Region. Malaria seropositivity had significant association with nPCR positivity [adjusted OR 10.0 (95% CI 3.2-29.4), P < 0.001]. Conclusion:Using nPCR the detection rate of malaria parasites increased by nearly threefold over rates based on microscopy in samples collected during a national cross-sectional survey in 2015 in Ethiopia. Such subpatent infections might contribute to malaria transmission. In addition to strengthening routine surveillance systems, malaria programmes may need to consider low-density, subpatent infections in order to accelerate malaria elimination efforts.

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Section: Discussionsupporting

confidence: 64%

Section: Study Areamentioning

confidence: 87%

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Assessment of subpatent Plasmodium infection in northwestern Ethiopia

Assefa

Ahmed

Deressa

et al. 2020

Malar J

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“…Despite the lack of a clearly defined relationship between antigen-matched targets from opposing expression systems, we remain confident that microarrays utilising IVTT or purified recombinant proteins are able to produce compelling and biologically relevant data. Indeed, our data show age-dependent trends in antibody responses (typical of highly endemic populations [1][2][3]) irrespective of expression system (Supplementary figure 2), lending weight to the applicability of either methodology in serological assays [33][34][35][36][37][38][39][40][41][42][43][44][45][46].…”

Section: Ama1 -Ivtt_1mentioning

confidence: 55%

Plasmodium falciparum serology: A comparison of two protein production methods for analysis of antibody responses by protein microarray

Oulton

Obiero²,

Rodríguez

et al. 2020

Preprint

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The evaluation of protein antigens as putative serologic biomarkers of infection has increasingly shifted to high-throughput, multiplex approaches such as the protein microarray. In vitro Transcription/Translation (IVTT) systems (a similarly high-throughput protein expression method) are already widely utilised in the production of protein microarrays, though purified recombinant proteins derived from more traditional whole cell based expression systems also play an important role in biomarker characterisation. Here we have performed a side-by-side comparison of antigen-matched protein targets from an IVTT and purified recombinant system, on a protein microarray. The magnitude and range of antibody responses to purified recombinants was found to be greater than that of IVTT proteins, and responses between targets from opposing expression systems did not clearly correlate. However, responses between amino acid sequence-matched targets from each expression system were more closely correlated. Despite the lack of a clearly defined relationship between antigen-matched targets produced in each expression system, our data indicate that protein microarrays produced using either method can be used confidently, in a context dependent manner, though care should be taken when comparing data derived from contrasting approaches.

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“…Proportion of seropositive for P. falciparum by region ranged from 11.0% in Somali to 65.0% (95% CI: 58.0-71.4) in Gambela Region (31). Given the lower prevalence of malaria in the anemia hotspot areas (eastern Ethiopia), it is less likely that malaria is the cause for the geospatial inequality of anemia in Ethiopia.…”

Section: Discussionmentioning

confidence: 99%

Geospatial Inequality of Anemia Among Children in Ethiopia

Endris

Dinant

Gebreyesus

et al. 2020

Preprint

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Background: Anemia remains a severe public health problem among children in Ethiopia. The lack of progress in the trend of anemia infers the failure of national anemia prevention and control programs. If there are considerable geospatial differences in the prevalence of anemia in Ethiopia, targeted approaches, based on the distribution and specific risk factors for that setting are needed to efficiently target health interventions. This study aimed to identify and locate anemia hotspots among children in Ethiopia. Methods: Data analysis was performed using Ethiopia Demographic and Health Survey (EDHS) 2016 Data. Blood specimens for anemia testing were collected from children age 6-59 months. Hemoglobin analyses were placed in a HemoCue photometer and the results were recorded onsite for 9,268 children. The outcome variable anemia was categorized into a dichotomous variable (anemic and not anemic); a child was considered as anemic if the blood-hemoglobin count was less than 11.0 g/dl. We applied Kulldorf’s spatial scan statistics and used SaTScanTM to identify locations and estimate cluster sizes. In addition, we ran LISA (local indicator of spatial association) and the Getis-Ord Gi(d) local statistics to detect and locate hotspots of anemia. We ran multilevel multivariable analysis to identify risk factors for anemia clustering.Result: More than half (57%) of children aged 6-59 months were anemic in Ethiopia. Higher prevalence of anemia was found among children who live in Somali region (83%), in rural area (58%), in the lowest wealth quintile (68%), and among children of mothers’ with no education (59%). We found significant geospatial inequality of anemia among children in Ethiopia. We identified one anemia cluster (hotspot) in the eastern part of Ethiopia. Women anemia, stunting and high fertility were associated with anemia clustering.Conclusion: Anemia clustering was found in the eastern part of Ethiopia. We recommend that policy makers and programmers should especially target this area for accelerated reduction of anemia.

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Multiplex serology demonstrate cumulative prevalence and spatial distribution of malaria in Ethiopia

Cited by 26 publications

References 32 publications

Assessment of subpatent Plasmodium infection in northwestern Ethiopia

Assessment of subpatent Plasmodium infection in northwestern Ethiopia

Plasmodium falciparum serology: A comparison of two protein production methods for analysis of antibody responses by protein microarray

Geospatial Inequality of Anemia Among Children in Ethiopia

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