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Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach – CORRIGENDUM
- Micah Cearns, Azmeraw T. Amare, Klaus Oliver Schubert, Anbupalam Thalamuthu, Joseph Frank, Fabian Streit, Mazda Adli, Nirmala Akula, Kazufumi Akiyama, Raffaella Ardau, Bárbara Arias, JeanMichel Aubry, Lena Backlund, Abesh Kumar Bhattacharjee, Frank Bellivier, Antonio Benabarre, Susanne Bengesser, Joanna M. Biernacka, Armin Birner, Clara Brichant-Petitjean, Pablo Cervantes, HsiChung Chen, Caterina Chillotti, Sven Cichon, Cristiana Cruceanu, Piotr M. Czerski, Nina Dalkner, Alexandre Dayer, Franziska Degenhardt, Maria Del Zompo, J. Raymond DePaulo, Bruno Étain, Peter Falkai, Andreas J. Forstner, Louise Frisen, Mark A. Frye, Janice M. Fullerton, Sébastien Gard, Julie S. Garnham, Fernando S. Goes, Maria Grigoroiu-Serbanescu, Paul Grof, Ryota Hashimoto, Joanna Hauser, Urs Heilbronner, Stefan Herms, Per Hoffmann, Andrea Hofmann, Liping Hou, Yi-Hsiang Hsu, Stephane Jamain, Esther Jiménez, Jean-Pierre Kahn, Layla Kassem, Po-Hsiu Kuo, Tadafumi Kato, John Kelsoe, Sarah Kittel-Schneider, Sebastian Kliwicki, Barbara König, Ichiro Kusumi, Gonzalo Laje, Mikael Landén, Catharina Lavebratt, Marion Leboyer, Susan G. Leckband, Mario Maj, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Mirko Manchia, Lina Martinsson, Michael J. McCarthy, Susan McElroy, Francesc Colom, Marina Mitjans, Francis M. Mondimore, Palmiero Monteleone, Caroline M. Nievergelt, Markus M. Nöthen, Tomas Novák, Claire O'Donovan, Norio Ozaki, Vincent Millischer, Sergi Papiol, Andrea Pfennig, Claudia Pisanu, James B. Potash, Andreas Reif, Eva Reininghaus, Guy A. Rouleau, Janusz K. Rybakowski, Martin Schalling, Peter R. Schofield, Barbara W. Schweizer, Giovanni Severino, Tatyana Shekhtman, Paul D. Shilling, Katzutaka Shimoda, Christian Simhandl, Claire M. Slaney, Alessio Squassina, Thomas Stamm, Pavla Stopkova, Fasil TekolaAyele, Alfonso Tortorella, Gustavo Turecki, Julia Veeh, Eduard Vieta, Stephanie H. Witt, Gloria Roberts, Peter P. Zandi, Martin Alda, Michael Bauer, Francis J. McMahon, Philip B. Mitchell, Thomas G. Schulze, Marcella Rietschel, Scott R. Clark, Bernhard T. Baune
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- Journal:
- The British Journal of Psychiatry / Volume 221 / Issue 2 / August 2022
- Published online by Cambridge University Press:
- 04 May 2022, p. 494
- Print publication:
- August 2022
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Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach
- Micah Cearns, Azmeraw T. Amare, Klaus Oliver Schubert, Anbupalam Thalamuthu, Joseph Frank, Fabian Streit, Mazda Adli, Nirmala Akula, Kazufumi Akiyama, Raffaella Ardau, Bárbara Arias, Jean-Michel Aubry, Lena Backlund, Abesh Kumar Bhattacharjee, Frank Bellivier, Antonio Benabarre, Susanne Bengesser, Joanna M. Biernacka, Armin Birner, Clara Brichant-Petitjean, Pablo Cervantes, Hsi-Chung Chen, Caterina Chillotti, Sven Cichon, Cristiana Cruceanu, Piotr M. Czerski, Nina Dalkner, Alexandre Dayer, Franziska Degenhardt, Maria Del Zompo, J. Raymond DePaulo, Bruno Étain, Peter Falkai, Andreas J. Forstner, Louise Frisen, Mark A. Frye, Janice M. Fullerton, Sébastien Gard, Julie S. Garnham, Fernando S. Goes, Maria Grigoroiu-Serbanescu, Paul Grof, Ryota Hashimoto, Joanna Hauser, Urs Heilbronner, Stefan Herms, Per Hoffmann, Andrea Hofmann, Liping Hou, Yi-Hsiang Hsu, Stephane Jamain, Esther Jiménez, Jean-Pierre Kahn, Layla Kassem, Po-Hsiu Kuo, Tadafumi Kato, John Kelsoe, Sarah Kittel-Schneider, Sebastian Kliwicki, Barbara König, Ichiro Kusumi, Gonzalo Laje, Mikael Landén, Catharina Lavebratt, Marion Leboyer, Susan G. Leckband, Mario Maj, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Mirko Manchia, Lina Martinsson, Michael J. McCarthy, Susan McElroy, Francesc Colom, Marina Mitjans, Francis M. Mondimore, Palmiero Monteleone, Caroline M. Nievergelt, Markus M. Nöthen, Tomas Novák, Claire O'Donovan, Norio Ozaki, Vincent Millischer, Sergi Papiol, Andrea Pfennig, Claudia Pisanu, James B. Potash, Andreas Reif, Eva Reininghaus, Guy A. Rouleau, Janusz K. Rybakowski, Martin Schalling, Peter R. Schofield, Barbara W. Schweizer, Giovanni Severino, Tatyana Shekhtman, Paul D. Shilling, Katzutaka Shimoda, Christian Simhandl, Claire M. Slaney, Alessio Squassina, Thomas Stamm, Pavla Stopkova, Fasil Tekola-Ayele, Alfonso Tortorella, Gustavo Turecki, Julia Veeh, Eduard Vieta, Stephanie H. Witt, Gloria Roberts, Peter P. Zandi, Martin Alda, Michael Bauer, Francis J. McMahon, Philip B. Mitchell, Thomas G. Schulze, Marcella Rietschel, Scott R. Clark, Bernhard T. Baune
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- Journal:
- The British Journal of Psychiatry / Volume 220 / Issue 4 / April 2022
- Published online by Cambridge University Press:
- 28 February 2022, pp. 219-228
- Print publication:
- April 2022
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Background
Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.
AimsTo use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.
MethodThis study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.
ResultsThe best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.
ConclusionsUsing PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
Characterisation of age and polarity at onset in bipolar disorder
- Janos L. Kalman, Loes M. Olde Loohuis, Annabel Vreeker, Andrew McQuillin, Eli A. Stahl, Douglas Ruderfer, Maria Grigoroiu-Serbanescu, Georgia Panagiotaropoulou, Stephan Ripke, Tim B. Bigdeli, Frederike Stein, Tina Meller, Susanne Meinert, Helena Pelin, Fabian Streit, Sergi Papiol, Mark J. Adams, Rolf Adolfsson, Kristina Adorjan, Ingrid Agartz, Sofie R. Aminoff, Heike Anderson-Schmidt, Ole A. Andreassen, Raffaella Ardau, Jean-Michel Aubry, Ceylan Balaban, Nicholas Bass, Bernhard T. Baune, Frank Bellivier, Antoni Benabarre, Susanne Bengesser, Wade H Berrettini, Marco P. Boks, Evelyn J. Bromet, Katharina Brosch, Monika Budde, William Byerley, Pablo Cervantes, Catina Chillotti, Sven Cichon, Scott R. Clark, Ashley L. Comes, Aiden Corvin, William Coryell, Nick Craddock, David W. Craig, Paul E. Croarkin, Cristiana Cruceanu, Piotr M. Czerski, Nina Dalkner, Udo Dannlowski, Franziska Degenhardt, Maria Del Zompo, J. Raymond DePaulo, Srdjan Djurovic, Howard J. Edenberg, Mariam Al Eissa, Torbjørn Elvsåshagen, Bruno Etain, Ayman H. Fanous, Frederike Fellendorf, Alessia Fiorentino, Andreas J. Forstner, Mark A. Frye, Janice M. Fullerton, Katrin Gade, Julie Garnham, Elliot Gershon, Michael Gill, Fernando S. Goes, Katherine Gordon-Smith, Paul Grof, Jose Guzman-Parra, Tim Hahn, Roland Hasler, Maria Heilbronner, Urs Heilbronner, Stephane Jamain, Esther Jimenez, Ian Jones, Lisa Jones, Lina Jonsson, Rene S. Kahn, John R. Kelsoe, James L. Kennedy, Tilo Kircher, George Kirov, Sarah Kittel-Schneider, Farah Klöhn-Saghatolislam, James A. Knowles, Thorsten M. Kranz, Trine Vik Lagerberg, Mikael Landen, William B. Lawson, Marion Leboyer, Qingqin S. Li, Mario Maj, Dolores Malaspina, Mirko Manchia, Fermin Mayoral, Susan L. McElroy, Melvin G. McInnis, Andrew M. McIntosh, Helena Medeiros, Ingrid Melle, Vihra Milanova, Philip B. Mitchell, Palmiero Monteleone, Alessio Maria Monteleone, Markus M. Nöthen, Tomas Novak, John I. Nurnberger, Niamh O'Brien, Kevin S. O'Connell, Claire O'Donovan, Michael C. O'Donovan, Nils Opel, Abigail Ortiz, Michael J. Owen, Erik Pålsson, Carlos Pato, Michele T. Pato, Joanna Pawlak, Julia-Katharina Pfarr, Claudia Pisanu, James B. Potash, Mark H Rapaport, Daniela Reich-Erkelenz, Andreas Reif, Eva Reininghaus, Jonathan Repple, Hélène Richard-Lepouriel, Marcella Rietschel, Kai Ringwald, Gloria Roberts, Guy Rouleau, Sabrina Schaupp, William A Scheftner, Simon Schmitt, Peter R. Schofield, K. Oliver Schubert, Eva C. Schulte, Barbara Schweizer, Fanny Senner, Giovanni Severino, Sally Sharp, Claire Slaney, Olav B. Smeland, Janet L. Sobell, Alessio Squassina, Pavla Stopkova, John Strauss, Alfonso Tortorella, Gustavo Turecki, Joanna Twarowska-Hauser, Marin Veldic, Eduard Vieta, John B. Vincent, Wei Xu, Clement C. Zai, Peter P. Zandi, Psychiatric Genomics Consortium (PGC) Bipolar Disorder Working Group, International Consortium on Lithium Genetics (ConLiGen), Colombia-US Cross Disorder Collaboration in Psychiatric Genetics, Arianna Di Florio, Jordan W. Smoller, Joanna M. Biernacka, Francis J. McMahon, Martin Alda, Bertram Müller-Myhsok, Nikolaos Koutsouleris, Peter Falkai, Nelson B. Freimer, Till F.M. Andlauer, Thomas G. Schulze, Roel A. Ophoff
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- Journal:
- The British Journal of Psychiatry / Volume 219 / Issue 6 / December 2021
- Published online by Cambridge University Press:
- 25 August 2021, pp. 659-669
- Print publication:
- December 2021
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Background
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
AimsTo examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
MethodGenome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
ResultsEarlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
ConclusionsAAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
P0140 - Age at onset in bipolar disorders
- A. Ortiz-Dominguez, C. Slaney, J. Garnham, M. Alda
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- Journal:
- European Psychiatry / Volume 23 / Issue S2 / April 2008
- Published online by Cambridge University Press:
- 16 April 2020, p. S233
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Background:
The underlying genetic heterogeneity in Bipolar Disorder (BD) has led to the search of potential markers associated with subtypes of the disorder; as such, age at onset (AAO) could be considered as a factor that defines more genetically homogeneous subgroups.
Objective:To analyze the modal distribution of a BD population according to the AAO of the disorder, as well as the clinical characteristics related to the distribution findings.
Methods:357 patients with a BD diagnosis were included in the study. AAO was defined as the age when the patient first met DSM-IV criteria for a major mood episode. Using an admixture analysis, patients were distributed among different parameters; and parametric analyses were conducted in order to compare the demographic and clinical characteristics between groups.
Results:The model that best fit the observed distribution was a mixture of three Gaussian distributions (mean ± SD): 17±3.7 years, 26±8.8 years, and 35.5±12.54 years. Statistically significant differences were found with respect to social status, course of illness, suicidal behavior, rapid cycling, medical co-morbidities and lithium response (p<0.05).
Conclusions:Our results support the existence of a tri-modal distribution in BD defined by AAO, each one with different clinical characteristics; and suggest that early-onset and late-onset BD reflect an underlying genetic heterogeneity in bipolar disorder, being early-onset BD implicitly a more serious subtype of disorder.
Larger right inferior frontal gyrus volume and surface area in participants at genetic risk for bipolar disorders
- V. Drobinin, C. Slaney, J. Garnham, L. Propper, R. Uher, M. Alda, T. Hajek
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- Journal:
- Psychological Medicine / Volume 49 / Issue 8 / June 2019
- Published online by Cambridge University Press:
- 30 July 2018, pp. 1308-1315
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Background
Larger grey matter volume of the inferior frontal gyrus (IFG) is among the most replicated biomarkers of genetic risk for bipolar disorders (BD). However, the IFG is a heterogeneous prefrontal region, and volumetric findings can be attributable to changes in cortical thickness (CT), surface area (SA) or gyrification. Here, we investigated the morphometry of IFG in participants at genetic risk for BD.
MethodsWe quantified the IFG cortical grey matter volume in 29 affected, 32 unaffected relatives of BD probands, and 42 controls. We then examined SA, CT, and cortical folding in subregions of the IFG.
ResultsWe found volumetric group differences in the right IFG, with the largest volumes in unaffected high-risk and smallest in control participants (F2,192 = 3.07, p = 0.01). The volume alterations were localized to the pars triangularis of the IFG (F2,97 = 4.05, p = 0.02), with no differences in pars opercularis or pars orbitalis. Pars triangularis volume was highly correlated with its SA [Pearson r(101) = 0.88, p < 0.001], which significantly differed between the groups (F2,97 = 4.45, p = 0.01). As with volume, the mean SA of the pars triangularis was greater in unaffected (corrected p = 0.02) and affected relatives (corrected p = 0.05) compared with controls. We did not find group differences in pars triangularis CT or gyrification.
ConclusionsThese findings strengthen prior knowledge about the volumetric findings in this region and provide a new insight into the localization and topology of IFG alterations. The unique nature of rIFG morphology in BD, with larger volume and SA early in the course of illness, could have practical implications for detection of participants at risk for BD.
The Simuliidae (Diptera) of British Honduras*
- D. J. Lewis, P. C. C. Garnham
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- Journal:
- Bulletin of Entomological Research / Volume 50 / Issue 4 / January 1960
- Published online by Cambridge University Press:
- 10 July 2009, pp. 703-710
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Several collections of pupae and adults of Simuliid Diptera were made in British Honduras between 9th January and 18th February 1958. Samples were collected in the Mountain Pine Ridge and El Cayo areas in the west, and along the highway traversing the eastern part of the country between Caves Branch and Stann Creek.
Thirteen species of Simulium were found, nine of which are named, including S. quadrivittatum Lw. and S. metallicum Bellardi which are very annoying biters. A, few observations on distribution and habits are recorded.
Of the two anthropophilic species of Simulium found, one is known to be a vector of onchocerciasis, if only of secondary importance, and the capability of the other to transmit the disease is unknown. The disease has apparently never been established in British Honduras and is present in Guatemala. The risk of infection to settlers moving into territory near Guatemala cannot be assessed without detailed knowledge of the epidemiology of the disease in Central America.
Final Results of an Experiment on the Control of Onchocerciasis by Eradication of the Vector
- P. C. C. Garnham, J. P. McMahon
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- Journal:
- Bulletin of Entomological Research / Volume 45 / Issue 1 / March 1954
- Published online by Cambridge University Press:
- 10 July 2009, pp. 175-176
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1. Disappearance of Simulium neavei after DDT-treatment of rivers in Kodera, Kenya, is still manifest after seven years, and the species seems to have been eradicated from the district.
2. Skin microfilaria rates have dropped from something under 7 per cent. to nil in the under 4 years age group; from 37 to 5 per cent. or less in the 4–8 years; and from 70 per cent. to 50 per cent. in adults.
3. The length of life of the adult worm can be at least seven years.
The Mosquitos of the Kaimosi Forest, Kenya Colony, with special Reference to Yellow Fever
- P. C. C. Garnham, J. O. Harper, R. B. Highton
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- Bulletin of Entomological Research / Volume 36 / Issue 4 / December 1946
- Published online by Cambridge University Press:
- 10 July 2009, pp. 473-496
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1. The danger of the establishment of yellow fever in certain of the forests of Kenya is pointed out. Kenya has had two recognised cases of the disease in recent years.
2. The Kaimosi forest was selected as a suitable area for investigation and the general environmental conditions are described.
3. A mosquito survey was undertaken over a period of two years and particular attention was paid to the question of “acrodendrophily” i.e., the preference shown by certain species of mosquitos for life in the tree-tops.
4. Five species of mosquitos—Culex nebulosus, Aëdes capensis, A. fraseri, A. deboeri subsp. demeilloni and A. longipalpis breed in high tree-holes; the last, almost entirely so. The many characteristically low breeders include A. aegypti and A. africanus. There is an interesting distinction between the two commoner Megarhines; M. brevipalpis breeds high, M. barbipes, low.
5. Four species of mosquitos—A. apicoargenteus, A. fraseri, A. africanus and A. longipalpis were found biting in the tree-tops; the last two being rare in ground catches.
6. Forest with a broken canopy proved best for adult catching and the morning was a better time than the (usually overcast) afternoon. Night searches gave negative results. Catches on high tree platforms appeared to be more prolific than those oa the ground.
7. The following points of special interest in regard to individual species of mosquitos are summarised below: —
(i) Megarhine larvae consume about 20 fourth-stage aegypti larvae a night. Pupal stage lasts on an average for nine days.
(ii) Aëdes aegypti breeds commonly in two sites (a) recently felled trees at forest edge; (b) rock pools in rivers in drought periods. Larvae are found a mile or more inside the forest. Breeding of this species has been discovered as high as 6,500 feet.
(iii) Aëdes apicoargenteus was the commonest adult. Some specimens survived 55 days in captivity.
(iv) Aëdes africanus shows a seasonal incidence, being commonest at the end of the “long rains”. Its favoured breeding places are the buttresses of the tree, Craibia elliottii.
(v) In the larval stage, Aëdes capensis is the commonest mosquito.
(vi) The characteristic breeding place of Theobaldia fraseri contained 79 parts of oxidisable matter per 100,000 of water.
8. Probably at least two trees per acre have rot holes with larvae and about 14 per cent, of the Dracaena plants are infested. Holes in shaded granite boulders are another common source of sylvan mosquitos.
9. Surveys of adjacent forest areas at different altitudes revealed striking changes in the mosquito fauna. Aëdes pulchrithorax is the prevalent species at the 6,500 foot level; A. kapretwae at the 8,500 foot; whilst in general, A. africanus, A. aegypti and A. bambusae appear to be widespread.
10. A study of the lists of mammals, trees and mosquitos indicates that the relict forest of Kaimosi contains numerous “western” species which are not found elsewhere so far to the east.
11. Immunity tests performed at the Yellow Fever Research Institute, Entebbe, demonstrated the absence of yellow fever in man and monkeys at Kaimosi. The monkeys show, however, immunity to Semliki forest virus and either Japanese B or St. Louis encephalitis virus.
12. The human inhabitants suffer from malaria and onchocerciasis (the latter carried by Simulium neavei) and the monkeys and fruit bats are infected with species of Plasmodium.
13. The Kaimosi forest from every standpoint (including meteorological) is suitable for the establishment of jungle yellow fever and possible measures of control ate briefly suggested.
14. Short descriptions of new species, etc., of mosquitos are given in the Appendix
The Eradication of Simulium neavei, Roubaud, from an Onchocerciasis Area in Kenya Colony
- P. C. C. Garnham, J. P. McMahon
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- Journal:
- Bulletin of Entomological Research / Volume 37 / Issue 4 / March 1947
- Published online by Cambridge University Press:
- 10 July 2009, pp. 619-628
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1. An onchocerciasis area in South Kavirondo, Kenya Colony, 65 square miles in extent, has been freed from Simulium neavei.
2. The fly was eliminated by the periodical application of DDT emulsion to all infested rivers and streams in the locality. Details of technique are described.
3. Most aquatic life, other than this species of Simulium, had returned to the treated streams, three months after the last application.
4. A microfilaria index of 37 per cent. in children aged four to eight was established as a base-line for future surveys.