Mosquito Alert impact summary

This is an impact report of the citizen science project Mosquito Alert. The scores displayed summarise the results of the assessment process designed by the MICS project. For more information on how they were calculated, visit https://mics.tools

Beta

Project Information

Project start date:
January 2014
Project Contacts:
Frederic Bartumeus - fbartu@ceab.csic.es
Project URL:
http://www.mosquitoalert.com/
Impact Assesment progress:
100% complete

Rules-based scores

These scores are calculated based on a set of rules written to combine a specific set of impact metrics on the same theme into a single indicator. A higher score means the project is carrying out more activities related to the theme of the indicator and is, therefore, more likely to have a higher positive impact in this area. Rule-based scores are only calculated for specific themes. Overall assessments can be found below in the machine-learning--based scoring. Descriptions and explanations of impact indicators are provided at about.mics.tools/indicators (e.g., the score is low on economic productivity because the project did not include specific aspects related to improving efficiency). Different scores trigger different recommendations presented in the following section. Also, scores are not linked to project objectives; they try to capture a broad range of impacts even if the project does not consider or care about all of them. All scores are out of 42.

Impact Indicators Impact score (max 42) Overall average
Society Activeness 18 36
Involvement 17 41
Governance Policy 38 4
Sustainable Development Goals 20 6
Economy Economic productivity 42 12
Financial sustainability 21 31
Environment Environmental awareness 16 11
Environmental footprint 11 39
Science and technology Scientific productivity 41 43
Interdiscplinary science 37 37

Recommendations

The following recommendations are determined by the scores the project received in the previous section. The recommendations are based on citizen-science best practice as defined in the current scientific literature and how other projects have taken action to improve their impact in specific areas. Of course, following these recommendations does not guarantee the project will suddenly have a higher impact; it all depends on the specific context of each project, but the might provide helpful inspiration.

Society Activeness

The activeness of participants within a project is an important aspect of citizen science. Activeness depends on participants being aware that they are contributing to a project, having a lot of responsibility in the project, and being satisfied with the process of participation. This project should ensure that all aspects of activeness have been considered.

Involvement

The degree of involvement of participants in a project is an important aspect of citizen science, and includes involving participants in multiple stages of the project, offering them multiple activities to take part in, and offering different levels of involvements depending on individual interests and availability. This project could consider whether there are more stages of the project that participants could be involved in for example by considering co-design or co-evaluation.

Governance Policy

The project is among the most successful on this platform at influencing policy. Congratulations! To get a score this high, the project must already have a lot of experience interacting with policy. But if the project wants to achieve the top scores for this indicator, it will have to consider and explicitly inform governmental policy at all scales (local, regional, national and global). Additionally, the project needs to be confident it has had an impact on external organisational policy and contributed to the enforcement of existing regulations or policies. It's a lot to ask, so don't be worried if the project is happy as it is, it has already achieved a lot!

Policy

The project is among the most successful on this platform at influencing policy. Congratulations! This suggests the project is quite exceptional in its interactions with policy makers. Maybe consider how you could share your experience with other projects so they can get inspiration and have similar success with policy influence?

Economy Economic productivity

It is great that the project has produced outputs that contribute to the economy through industry, commerce, innovation or technological development. If you haven't already, it might be worth considering any legal implications through a dedicated IPR plan.

Financial sustainability

You are on the right path! It is clear that the project has considered its financial sustainability into the future. However, there could be more to do. If one does not already exist, an exploitation plan could help sustain project outputs, whilst considering open-source software and tools could reduce costs.

Environment Environmental footprint

This indicator considers the project's material footprint, polluting emissions, procurement policy, and pro-environmental actions for participants (such as litter picking). The project's score for this indicator shows that the project has considered some of these elements but to get a higher score the project needs to take measures to improve its environmental footprint in all these areas. 

Environmental awareness

The project clearly promotes environmental awareness, by educating participants on environmental challenges, or by contributing to participants' awareness of the natural environment through dissemination activities. Want to be able to measure participants' higher awareness, or increased stewardship? You might want to consider this paper.

Science and technology Scientific productivity

Congratulations - in a world of "publish or perish", this project has high scientific productivity. With a large number of publications in high impact-factor journals, the project's research has been well cited, indicating outcomes have been widely shared.

Interdiscplinary science

By working across multiple disciplines , this project is making efforts to promote interdisciplinary ways of working. There is evidence that interdisciplinarity is statistically significantly and positively associated with research impact (Okamura, 2019), largely through the engagement of a wider audience. Keep up the good work!

Machine Learning Scores

The following scores were calculated using a statistically-driven machine-learning approach, a type of AI that learns to perform a task by analysing patterns in data. This is an experimental approach to citizen-science impact assessment, and the exact reasoning behind the scores is not explainable. The scores represent a best guess of the impact the project is having in each domain. How can you use the score? Well, this platform gives a common framework for impact assessment so you can use the scores: to see how the project's impact evolves over time; to compare the project with others; to report to funders and participants; or for your organisation's internal reporting. All scores are out of 42.

Society 8 Society 8 Governance 24 Governance 24 Economy 24 Economy 24 Environment 25 Environment 25 Science and technology 20 Science and technology 20 max. 42
Total Score 20/42