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Protocol for the crowdsourced image-based morbidity hotspot surveillance for neglected tropical diseases (CIMS-NTDs)
Efficient NTDs elimination strategies require effective surveillance and targeted interventions. Traditional methods are costly and time-consuming, often failing to cover entire populations in case of movement restrictions. To address these challenges, a morbidity image-based surveillance system is...
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Published in: | PloS one 2024-05, Vol.19 (5), p.e0303179-e0303179 |
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description | Efficient NTDs elimination strategies require effective surveillance and targeted interventions. Traditional methods are costly and time-consuming, often failing to cover entire populations in case of movement restrictions. To address these challenges, a morbidity image-based surveillance system is being developed. This innovative approach which leverages the smartphone technology aims at simultaneous surveillance of multiple NTDs, enhancing cost-efficiency, reliability, and community involvement, particularly in areas with movement constraints. Moreover, it holds promise for post-elimination surveillance.
The pilot of this method will be conducted across three states in southern Nigeria. It will target people affected by Neglected Tropical Diseases and members of their communities. The new surveillance method will be introduced to target communities in the selected states through community stakeholder's advocacy meetings and awareness campaigns. The pilot which is set to span eighteen months, entails sensitizing NTDs-affected individuals and community members using signposts, posters, and handbills, to capture photos of NTDs manifestations upon notice using smartphones. These images, along with pertinent demographic information, will be transmitted to a dedicated server through WhatsApp or Telegram accounts. The received images will be reviewed and organized at backend and then forwarded to a panel of experts for identification and annotation to specific NTDs. Data generated, along with geocoordinate information, will be used to create NTDs morbidity hotspot maps using ArcGIS. Accompanying metadata will be used to generate geographic and demographic distributions of various NTDs identified. To protect privacy, people will be encouraged to send manifestation photos of the affected body part only without any identifiable features.
NTDs prevalence data obtained using conventional surveillance methods from both the pilot and selected control states during the pilot period will be compared with data from the CIMS-NTDs method to determine its effectiveness.
It is expected that an effective, privacy-conscious, population inclusive new method for NTDs surveillance, with the potential to yield real-time data for the identification of morbidity hotspots and distribution patterns of NTDs will be established. The results will provide insights into the effectiveness of the new surveillance method in comparison to traditional approaches, potentially advancing NTDs elim |
doi_str_mv | 10.1371/journal.pone.0303179 |
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The pilot of this method will be conducted across three states in southern Nigeria. It will target people affected by Neglected Tropical Diseases and members of their communities. The new surveillance method will be introduced to target communities in the selected states through community stakeholder's advocacy meetings and awareness campaigns. The pilot which is set to span eighteen months, entails sensitizing NTDs-affected individuals and community members using signposts, posters, and handbills, to capture photos of NTDs manifestations upon notice using smartphones. These images, along with pertinent demographic information, will be transmitted to a dedicated server through WhatsApp or Telegram accounts. The received images will be reviewed and organized at backend and then forwarded to a panel of experts for identification and annotation to specific NTDs. Data generated, along with geocoordinate information, will be used to create NTDs morbidity hotspot maps using ArcGIS. Accompanying metadata will be used to generate geographic and demographic distributions of various NTDs identified. To protect privacy, people will be encouraged to send manifestation photos of the affected body part only without any identifiable features.
NTDs prevalence data obtained using conventional surveillance methods from both the pilot and selected control states during the pilot period will be compared with data from the CIMS-NTDs method to determine its effectiveness.
It is expected that an effective, privacy-conscious, population inclusive new method for NTDs surveillance, with the potential to yield real-time data for the identification of morbidity hotspots and distribution patterns of NTDs will be established. The results will provide insights into the effectiveness of the new surveillance method in comparison to traditional approaches, potentially advancing NTDs elimination strategies.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0303179</identifier><identifier>PMID: 38728272</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Annotations ; Artificial intelligence ; Body parts ; Cellular telephones ; Community ; Community involvement ; Crowdsourcing ; Crowdsourcing - methods ; Demographics ; Demography ; Distribution patterns ; Effectiveness ; Feedback ; Health facilities ; Health surveillance ; Humans ; Intervention ; Morbidity ; Neglected Diseases - epidemiology ; NGOs ; Nigeria - epidemiology ; Nongovernmental organizations ; Pilot Projects ; Population Surveillance - methods ; Privacy ; Real time ; Research hot spots ; Sensitizing ; Smart phones ; Smartphone ; Smartphones ; Surveillance systems ; Tropical diseases ; Tropical Medicine - methods</subject><ispartof>PloS one, 2024-05, Vol.19 (5), p.e0303179-e0303179</ispartof><rights>Copyright: © 2024 Chukwuocha et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2024 Public Library of Science</rights><rights>2024 Chukwuocha et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 Chukwuocha et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c586t-aed3cbae3c8e6280f28f4e4e8ec345e8f44e1a0f0aeb0d08547addc8ce40a1e23</cites><orcidid>0000-0002-4986-6847 ; 0000-0002-6670-6087</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/3069286700/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/3069286700?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25751,27922,27923,37010,37011,38514,43893,44588,74182,74896</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38728272$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Yaro, Clement Ameh</contributor><creatorcontrib>Chukwuocha, Uchechukwu Madukaku</creatorcontrib><creatorcontrib>Oyamienlen, Christopher Sule</creatorcontrib><creatorcontrib>Bosede, Ayoola Oluwaseun</creatorcontrib><creatorcontrib>Dozie, Ikechukwu Nosike</creatorcontrib><title>Protocol for the crowdsourced image-based morbidity hotspot surveillance for neglected tropical diseases (CIMS-NTDs)</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Efficient NTDs elimination strategies require effective surveillance and targeted interventions. Traditional methods are costly and time-consuming, often failing to cover entire populations in case of movement restrictions. To address these challenges, a morbidity image-based surveillance system is being developed. This innovative approach which leverages the smartphone technology aims at simultaneous surveillance of multiple NTDs, enhancing cost-efficiency, reliability, and community involvement, particularly in areas with movement constraints. Moreover, it holds promise for post-elimination surveillance.
The pilot of this method will be conducted across three states in southern Nigeria. It will target people affected by Neglected Tropical Diseases and members of their communities. The new surveillance method will be introduced to target communities in the selected states through community stakeholder's advocacy meetings and awareness campaigns. The pilot which is set to span eighteen months, entails sensitizing NTDs-affected individuals and community members using signposts, posters, and handbills, to capture photos of NTDs manifestations upon notice using smartphones. These images, along with pertinent demographic information, will be transmitted to a dedicated server through WhatsApp or Telegram accounts. The received images will be reviewed and organized at backend and then forwarded to a panel of experts for identification and annotation to specific NTDs. Data generated, along with geocoordinate information, will be used to create NTDs morbidity hotspot maps using ArcGIS. Accompanying metadata will be used to generate geographic and demographic distributions of various NTDs identified. To protect privacy, people will be encouraged to send manifestation photos of the affected body part only without any identifiable features.
NTDs prevalence data obtained using conventional surveillance methods from both the pilot and selected control states during the pilot period will be compared with data from the CIMS-NTDs method to determine its effectiveness.
It is expected that an effective, privacy-conscious, population inclusive new method for NTDs surveillance, with the potential to yield real-time data for the identification of morbidity hotspots and distribution patterns of NTDs will be established. The results will provide insights into the effectiveness of the new surveillance method in comparison to traditional approaches, potentially advancing NTDs elimination strategies.</description><subject>Analysis</subject><subject>Annotations</subject><subject>Artificial intelligence</subject><subject>Body parts</subject><subject>Cellular telephones</subject><subject>Community</subject><subject>Community involvement</subject><subject>Crowdsourcing</subject><subject>Crowdsourcing - methods</subject><subject>Demographics</subject><subject>Demography</subject><subject>Distribution patterns</subject><subject>Effectiveness</subject><subject>Feedback</subject><subject>Health facilities</subject><subject>Health surveillance</subject><subject>Humans</subject><subject>Intervention</subject><subject>Morbidity</subject><subject>Neglected Diseases - epidemiology</subject><subject>NGOs</subject><subject>Nigeria - epidemiology</subject><subject>Nongovernmental organizations</subject><subject>Pilot Projects</subject><subject>Population Surveillance - methods</subject><subject>Privacy</subject><subject>Real time</subject><subject>Research hot spots</subject><subject>Sensitizing</subject><subject>Smart phones</subject><subject>Smartphone</subject><subject>Smartphones</subject><subject>Surveillance systems</subject><subject>Tropical diseases</subject><subject>Tropical Medicine - methods</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>COVID</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqNkktv1DAUhSMEoqXwDxBEQkLtIoMTJ7azrIbXSIUiWthaN_bNjEeZOLUdoP8eTyetOqgL5IUf-s699vFJkpc5meWU5-_WdnQ9dLPB9jgjlNCc14-Sw7ymRcYKQh_fWx8kz7xfE1JRwdjT5IAKXoiCF4dJ-OZssMp2aWtdGlaYKmd_ax-LK9Sp2cASswZ8XG-sa4w24Tpd2eAHG1I_ul9oug56hTf6HpcdqhDh4OxgFHSpNh6j3KfH88WXi-zr5Xt_8jx50kLn8cU0HyU_Pn64nH_Ozs4_LeanZ5mqBAsZoKaqAaRKICsEaQvRlliiQEXLCuOmxBxISwAboomoSg5aK6GwJJBjQY-S17u6Q2e9nAzzkhJWF4JxQiKx2BHawloOLr7XXUsLRt4cWLeU4IJRHUquOLBW5BqLpgRgddk0TIGo65ZVKuex1vHUzdmrEX2QG-MVbu1BO27bVrTmpK7riL75B334chO1hNjf9K0NDtS2qDzlNaU8fjmL1OwBKg6NG6NiOFoTz_cEJ3uCyAT8E5Ywei8XF9__nz3_uc--vceuELqw8rYbg7G93wfLHRij5r3D9s74nMhttm_dkNtsyynbUfZqMm1sNqjvRLdhpn8Blr_1Cg</recordid><startdate>20240510</startdate><enddate>20240510</enddate><creator>Chukwuocha, Uchechukwu Madukaku</creator><creator>Oyamienlen, Christopher Sule</creator><creator>Bosede, Ayoola Oluwaseun</creator><creator>Dozie, Ikechukwu Nosike</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>COVID</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-4986-6847</orcidid><orcidid>https://orcid.org/0000-0002-6670-6087</orcidid></search><sort><creationdate>20240510</creationdate><title>Protocol for the crowdsourced image-based morbidity hotspot surveillance for neglected tropical diseases (CIMS-NTDs)</title><author>Chukwuocha, Uchechukwu Madukaku ; Oyamienlen, Christopher Sule ; Bosede, Ayoola Oluwaseun ; Dozie, Ikechukwu Nosike</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c586t-aed3cbae3c8e6280f28f4e4e8ec345e8f44e1a0f0aeb0d08547addc8ce40a1e23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Analysis</topic><topic>Annotations</topic><topic>Artificial intelligence</topic><topic>Body parts</topic><topic>Cellular telephones</topic><topic>Community</topic><topic>Community involvement</topic><topic>Crowdsourcing</topic><topic>Crowdsourcing - 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Traditional methods are costly and time-consuming, often failing to cover entire populations in case of movement restrictions. To address these challenges, a morbidity image-based surveillance system is being developed. This innovative approach which leverages the smartphone technology aims at simultaneous surveillance of multiple NTDs, enhancing cost-efficiency, reliability, and community involvement, particularly in areas with movement constraints. Moreover, it holds promise for post-elimination surveillance.
The pilot of this method will be conducted across three states in southern Nigeria. It will target people affected by Neglected Tropical Diseases and members of their communities. The new surveillance method will be introduced to target communities in the selected states through community stakeholder's advocacy meetings and awareness campaigns. The pilot which is set to span eighteen months, entails sensitizing NTDs-affected individuals and community members using signposts, posters, and handbills, to capture photos of NTDs manifestations upon notice using smartphones. These images, along with pertinent demographic information, will be transmitted to a dedicated server through WhatsApp or Telegram accounts. The received images will be reviewed and organized at backend and then forwarded to a panel of experts for identification and annotation to specific NTDs. Data generated, along with geocoordinate information, will be used to create NTDs morbidity hotspot maps using ArcGIS. Accompanying metadata will be used to generate geographic and demographic distributions of various NTDs identified. To protect privacy, people will be encouraged to send manifestation photos of the affected body part only without any identifiable features.
NTDs prevalence data obtained using conventional surveillance methods from both the pilot and selected control states during the pilot period will be compared with data from the CIMS-NTDs method to determine its effectiveness.
It is expected that an effective, privacy-conscious, population inclusive new method for NTDs surveillance, with the potential to yield real-time data for the identification of morbidity hotspots and distribution patterns of NTDs will be established. The results will provide insights into the effectiveness of the new surveillance method in comparison to traditional approaches, potentially advancing NTDs elimination strategies.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>38728272</pmid><doi>10.1371/journal.pone.0303179</doi><tpages>e0303179</tpages><orcidid>https://orcid.org/0000-0002-4986-6847</orcidid><orcidid>https://orcid.org/0000-0002-6670-6087</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Analysis Annotations Artificial intelligence Body parts Cellular telephones Community Community involvement Crowdsourcing Crowdsourcing - methods Demographics Demography Distribution patterns Effectiveness Feedback Health facilities Health surveillance Humans Intervention Morbidity Neglected Diseases - epidemiology NGOs Nigeria - epidemiology Nongovernmental organizations Pilot Projects Population Surveillance - methods Privacy Real time Research hot spots Sensitizing Smart phones Smartphone Smartphones Surveillance systems Tropical diseases Tropical Medicine - methods |
title | Protocol for the crowdsourced image-based morbidity hotspot surveillance for neglected tropical diseases (CIMS-NTDs) |
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