| Literature DB >> 25164687 |
Heven Sime, Kebede Deribe1, Ashenafi Assefa, Melanie J Newport, Fikre Enquselassie, Abeba Gebretsadik, Amha Kebede, Asrat Hailu, Oumer Shafi, Abraham Aseffa, Richard Reithinger, Simon J Brooker, Rachel L Pullan, Jorge Cano, Kadu Meribo, Alex Pavluck, Moses J Bockarie, Maria P Rebollo, Gail Davey.
Abstract
BACKGROUND: The World Health Organization (WHO), international donors and partners have emphasized the importance of integrated control of neglected tropical diseases (NTDs). Integrated mapping of NTDs is a first step for integrated planning of programmes, proper resource allocation and monitoring progress of control. Integrated mapping has several advantages over disease specific mapping by reducing costs and enabling co-endemic areas to be more precisely identified. We designed and conducted integrated mapping of lymphatic filariasis (LF) and podoconiosis in Ethiopia; here we present the methods, challenges and lessons learnt.Entities:
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Year: 2014 PMID: 25164687 PMCID: PMC4153915 DOI: 10.1186/1756-3305-7-397
Source DB: PubMed Journal: Parasit Vectors ISSN: 1756-3305 Impact factor: 3.876
Figure 1Sampling framework for LF and podoconiosis mapping in Ethiopia, 2013.
Data collectors’ perceptions of data collection using smartphones
| Aspect | Perception |
|---|---|
| Time | Saves time during data collection through automated skip patterns. |
| Saves time during entry: paper-based data collection requires double data entry. | |
| Writing on a smartphone is easier than writing on paper. | |
| Data quality | Some restrictive rules reduced error. For example, it was impossible to enter age less than 15 years. |
| The skip pattern reduced error in entering irrelevant data. | |
| Transport and logistics | Easy to carry compared with thousands of questionnaires. |
| Reduces duplication, stamping and transportation. Smartphones are handy and easily portable. | |
| Data storage | Send data instantly. However in case of lack of network access data must be stored and could be lost. |
| Paper based data are difficult to keep clean. | |
| Communication | Unless you explain to the respondents, they may think that you are playing a game or not fully attending when you are entering data onto a smartphone. |
| People are more familiar with paper and would be more comfortable to respond to questions. | |
| Feedback mechanism | Feedback is received on a regular basis, since the data managers at central level have access to the completed data instantly. In paper-based data collection you have to wait until a supervisor comes and collects the questionnaire. |
| Other concerns | Charging in areas where there is no electricity is difficult. |
| Smartphone are costly and may attract robbery. | |
| Once data are sent there is no room to correct, unless you contact people in the central level. |
Figure 2Clinical algorithm for podoconiosis diagnosis. There is no point-of-care diagnostic tool for podoconiosis. Currently, podoconiosis is a diagnosis of clinical exclusion based on history, physical examination and certain disease-specific tests to exclude common differential diagnoses. All individuals included in the survey were tested for circulating W. bancrofti antigen using an ICT. Those found to be positive, regardless of the presence or absence of lymphoedema, were excluded from further clinical examination for podoconiosis. The common differential diagnoses of podoconiosis are lymphoedema due to LF, systemic disease and leprosya. The differentiation of podoconiosis from LF used a panel approach, including clinical history, physical examination, antigen and antibody tests. The swelling of podoconiosis starts in the foot and progresses upwards, whereas the swelling in LF starts elsewhere in the leg. Podoconiosis lymphoedema is asymmetric, usually confined to below the knees, and unlikely to involve the groin. In contrast, lymphoedema due to LF is commonly unilateral and extends above the knee, usually with groin involvement. In addition to the clinical history and physical examination, an antigen-based ICT was used to distinguish between the two causes of lymphoedema, although the majority of LF patients are also negative for the antigen-based test. To distinguish between podoconiosis and leprosy, clinical history and physical examination was used. Patients were asked if they had been diagnosed with leprosy and physical examination was conducted to exclude signs of leprosy including sensory loss. Onchocerciasis has clear clinical features which can easily be distinguished from podoconiosis. All lymphoedema cases were examined for signs of onchocerciasis. Systemic causes of lymphoedema were ruled out by examination of other organ systems. Hereditary causes of lymphoedema were excluded since they occur at birth or immediately after birth, whereas podoconiosis requires extended exposure to red clay soil.
Figure 3Mapping survey setup. Each individual participating in the survey was registered and gave informed written consent. Then they were assigned an in individuals ID and were given a card. The participants retained the card throughout the survey. Then ICT test were conducted, followed by podoconiosis and LF questioner. Finally ICT test results were provided to each individual.
Budgets and actual costs of LF and podoconiosis mapping in Ethiopia
| Item | LF only mapping (originally budgeted) | Podoconiosis only mapping (originally budgeted) | Integrated mapping (actual expenditures) | |||
|---|---|---|---|---|---|---|
| Description | Amount(US$) | Description | Amount(US$) | Description | Amount(US$) | |
| Training | For 102 data collectors (without 34 podoconiosis nurses) | 12,958 | For 102 data collectors | 12,958 | For 102 data collectors + 34 Nurses | 17,278 |
| Personnel | For 102 data collectors(central), supervisors, drivers, and local data collectors (without 34 podoconiosis nurses) | 350,376 | For 102 data collectors(central), supervisors and drivers, and local data collectors ( without 34 nurses for LF) | 350,376 | For 102 data collectors(central), supervisors and drivers, and local data collectors | 419,793 |
| Vehicle rent | For each team (34 teams) | 269,100 | For each team (34 teams) | 269,100 | For each team (34 teams) | 269,100 |
| Fuel | 27,961 | 27,961 | 27,961 | |||
| ICT cards | 399,800 | 399,800 | 399,800 | |||
| Mobile phones | 44 mobile phones (without 40 mobile phone for podoconiosis data collection) | 6,000 | 40 mobile phones | 5,454 | 84 mobile phone | 11,454 |
| Other mapping supplies | 81,045 | 810,45 | 81,045 | |||
| Data management | 1,667 | 1,667 | 1,667 | |||
| Result dissemination and project execution | 18,302 | 18,302 | 18,302 | |||
| Bench Fee | 45,000 | 45,000 | 45,000 | |||
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Challenges and solutions taken during the mapping
| Challenges | Solutions taken |
|---|---|
| Batteries running out of charge | Charge all the chargers after work and prepare them for the next day. Use of car charger in areas where there is no electricity. In a few cases where charging was not possible, paper based data collection were conducted for one day, while the other team members charged the smartphones in nearby towns. |
| Inability to edit once data is submitted in the smartphone. | Communicate with the central team to discuss any errors and edit the data promptly. |
| Lack of network | Store the data in the smartphone and transfer when there is access for internet. |
| Community mobilization | Discuss the best time for the community for mass gathering, such as early in the morning or late in the afternoon. Whenever appropriate, use holidays. |
| Inaccessibility (some districts during rainy season) | Use alternative transport such as motorbikes, boat or horses. In areas where no other possibilities existed, walking was the last resort. |