The objective of this study is to gain a comparative understanding of spatial determinants for outreach and clinic vaccination, which is critical for operationalizing efforts and breaking down structural biases; particularly relevant in countries where resources are low, and sub-region variance is high. Leveraging a massive effort to digitize public system reporting by Lady and Community Health Workers (CHWs) with geo-located data on over 4 million public-sector vaccinations from September 2017 through 2019, understanding health service operations in relation to vulnerable spatial determinants were made feasible. Location and type of vaccinations (clinic or outreach) were compared to regional spatial attributes where they were performed. Important spatial attributes were assessed using three modeling approaches (ridge regression, gradient boosting, and a generalized additive model). Consistent predictors for outreach, clinic, and proportion of third dose pentavalent vaccinations by region were identified. Of all Penta-3 vaccination records, 86.3% were performed by outreach efforts. At the tehsil level (fourth-order administrative unit), controlling for child population, population density, proportion of population in urban areas, distance to cities, average maternal education, and other relevant factors, increased poverty was significantly associated with more in-clinic vaccinations (β = 0.077), and lower proportion of outreach vaccinations by region (β = -0.083). Analyses at the union council level (fifth-administrative unit) showed consistent results for the differential importance of poverty for outreach versus clinic vaccination. Relevant predictors for each type of vaccination (outreach vs. in-clinic) show how design of outreach vaccination can effectively augment vaccination efforts beyond healthcare services through clinics. As Pakistan is third among countries with the most unvaccinated and under-vaccinated children, understanding barriers and factors associated with vaccination can be demonstrative for other national and sub-national regions facing challenges and also inform guidelines on supporting CHWs in health systems.

Using two RCTs in middle schools in Pakistan, we show that brief, expert-led, curriculum-based videos integrated into the classroom experience improved teaching effectiveness: student test scores in math and science increased by 0.3 standard deviations, 60 percent more than the control group, after 4 months of exposure. Students and teachers increased their attendance, and students were more likely to pass the high-stakes government exams. By contrast, providing similar content to students on personal tablets decreased student scores by 0.4 SD. The contrast between the two effects shows the importance of engaging teachers and the potential for technology to do so. (JEL I21, I28, J45, O15, O30)

Is it possible to identify crime suspects by their mobile phone call records? Can the spatial-temporal movements of individuals linked to convicted criminals help to identify those who facilitate crime? Might we leverage the usage of mobile phones, such as incoming and outgoing call numbers, coordinates, call duration and frequency of calls, in a specific time window on either side of a crime to provide a focus for the location and period under investigation? Might the call data records of convicted criminals' social networks serve to distinguish criminals from non-criminals? To address these questions, we used heterogeneous call data records dataset by tapping into the power of social network analysis and the advancements in graph convolutional networks. In collaboration with the Punjab Police and Punjab Information Technology Board, these techniques were useful in identifying convicted individuals. The approaches employed are useful in identifying crime suspects and facilitators to support smart policing in the fight against the country's increasing crime rates. Last but not least, the applied methods are highly desirable to complement high-cost video-based smart city surveillance platforms in developing countries.

Increasing urbanization is having a profound effect on infectious disease risk, posing significant challenges for governments to allocate limited resources for their optimal control at a sub-city scale. With recent advances in data collection practices, empirical evidence about the efficacy of highly localized containment and intervention activities, which can lead to optimal deployment of resources, is possible. However, there are several challenges in analyzing data from such real-world observational settings. Using data on 3.9 million instances of seven dengue vector containment activities collected between 2012 and 2017, here we develop and assess two frameworks for understanding how the generation of new dengue cases changes in space and time with respect to application of different types of containment activities. Accounting for the non-random deployment of each containment activity in relation to dengue cases and other types of containment activities, as well as deployment of activities in different epidemiological contexts, results from both frameworks reinforce existing knowledge about the efficacy of containment activities aimed at the adult phase of the mosquito lifecycle. Results show a 10% (95% CI: 1-19%) and 20% reduction (95% CI: 4-34%) reduction in probability of a case occurring in 50 meters and 30 days of cases which had Indoor Residual Spraying (IRS) and fogging performed in the immediate vicinity, respectively, compared to cases of similar epidemiological context and which had no containment in their vicinity. Simultaneously, limitations due to the real-world nature of activity deployment are used to guide recommendations for future deployment of resources during outbreaks as well as data collection practices. Conclusions from this study will enable more robust and comprehensive analyses of localized containment activities in resource-scarce urban settings and lead to improved allocation of resources of government in an outbreak setting.

Religious donations are a very significant financial resource, and mosques as places of worship and as religious institutions, play a strong role in collecting such donations. This is especially true in developing countries, where cash-based donations are commonplace. In this paper, through 8 semi-structured interviews with mosque leaders (Imams) and finance secretaries, and three religious and government leaders, we present qualitative findings about various donation mechanisms and the religious and legal regulations governing such transactions. We then use these findings to present suggestions for a mobile-based application that digitizes the donation mechanism for local mosques.

research-article Share on The internet of the orals Authors: Aditya Vashistha Cornell University, Ithaca, NY Cornell University, Ithaca, NYView Profile , Umar Saif ICTD, Lahore, Pakistan ICTD, Lahore, PakistanView Profile , Agha Ali Raza Information Technology University, Lahore, Pakistan Information Technology University, Lahore, PakistanView Profile Authors Info & Claims Communications of the ACMVolume 62Issue 11November 2019 pp 100–103https://doi.org/10.1145/3343452Published:24 October 2019Publication History 4citation3,203DownloadsMetricsTotal Citations4Total Downloads3,203Last 12 Months119Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

The global population at risk of mosquito-borne diseases such as dengue, yellow fever, chikungunya and Zika is expanding. Infectious disease models commonly incorporate environmental measures like temperature and precipitation. Given increasing availability of high-resolution satellite imagery, here we consider including landscape features from satellite imagery into infectious disease prediction models. To do so, we implement a Convolutional Neural Network (CNN) model trained on Imagenet data and labelled landscape features in satellite data from London. We then incorporate landscape features from satellite image data from Pakistan, labelled using the CNN, in a well-known Susceptible-Infectious-Recovered epidemic model, alongside dengue case data from 2012-2016 in Pakistan. We study improvement of the prediction model for each of the individual landscape features, and assess the feasibility of using image labels from a different place. We find that incorporating satellite-derived landscape features can improve prediction of outbreaks, which is important for proactive and strategic surveillance and control programmes.

Information dissemination using automated phone calls allows reaching low-literate and tech-naive populations. Open challenges include rapid verification of expected knowledge gaps in the community, dissemination of specific information to address these gaps, and follow-up measurement of knowledge retention. We report Sawaal, a voice-based telephone service that uses audio-quizzes to address these challenges. Sawaal allows its open community of users to post and attempt multiple-choice questions and to vote and comment on them. Sawaal spreads virally as users challenge friends to quiz competitions. Administrator-posted questions allow confirming specific knowledge gaps, spreading correct information and measuring knowledge retention via rephrased, repeated questions. In 14 weeks and with no advertisement, Sawaal reached 3,433 users (120,119 calls) in Pakistan, who contributed 13,276 questions that were attempted 455,158 times by 2,027 users. Knowledge retention remained significant for up to two weeks. Surveys revealed that 71% of the mostly low-literate, young, male users were blind.

Speech is more natural than text for a large part of the world including hard-to-reach populations (low-literate, poor, tech-novice, visually-impaired, marginalized) and oral cultures. Voice-based services over simple mobile phones are effective means to provide orality-driven social connectivity to such populations. We present Baang, a versatile and inclusive voice-based social platform that allows audio content creation and sharing among its open community of users. Within 8 months, Baang spread virally to 10,721 users (69% of them blind) who participated in 269,468 calls and shared their thoughts via 44,178 audio-posts, 343,542 votes, 124,389 audio-comments and 94,864 shares. We show that the ability to vote, comment and share leads to viral spread, deeper engagement, longer retention and emergence of true dialog among participants. Beyond connectivity, Baang provides its users with a voice and a social identity as well as means to share information and get community support.

We present a novel technique for rapid collection of spontaneous speech data over mobile phone channel using telephonic community forums. Our public forum allows users to post audio messages, listen to messages posted by others, post votes and audio comments, and share content with friends through subsidized phone calls. The entertainment aspects and sharing features of the forum lead to its viral spread in Pakistan. Within 8 months, it reached 11,017 users and gathered 1,207 hours of speech data comprising 57,454 audio-posts and 130,685 audio comments, spanning Urdu and 9 regional languages. We trained an ASR using just 9.5 hours of the corpus to obtain 24.19% WER. Community forums automatically overcome common spontaneous speech data collection challenges like speaker recruitment, natural speech elicitation, content diversity, informed consent, sampling real-world ambient noise, and reach (for geographically remote linguistic communities). This technique is especially useful for gathering speech corpora for underresourced languages hence enabling the development of speech recognition, keyword spotting, speaker ID, and noise classification systems (among others) for such languages. It also allows rapid, automatic preservation of spoken languages and oral aspects of culture. This technique can be extended to collect speech data for endangered languages, oral cultures, and linguistic minorities.

Dengue virus causes over 96 million cases worldwide per year and is ex-panding rapidly in geographic range, especially in urban areas. Containment activities are an essential part of reducing the public health burden caused by dengue, but systematic evidence on the comparative efficacy of activities from the field is lacking. To our knowledge, the effect of containment activities on local (sub-city) scale disease dynamics has never been systematically characterized using empirical containment and case data. We combine data from a comprehensive dengue containment monitoring system with confirmed dengue case data from the local government hospitals to estimate the efficacy of seven common containment activities in two urban areas in Pakistan. We use a modified version of the time series Suspected Infected Recovered frame-work to estimate how the reproductive number, R0, of the outbreak changed in relation to deployment of each containment activity. We also estimate the spatial dependence of cases based on deployment of each containment activity. Both analyses suggest that activities aimed at the adult phase of the mosquito lifecycle have the highest efficacy, with fogging having the largest quantifiable effect in reducing cases immediately after deployment. In examining the efficacy of containment activities contemporaneously deployed in the same locations, results here can guide recommendations for future deployment of resources during dengue outbreaks in urban settings.

This paper explores the use of Interactive Voice Response (IVR) systems for automatic surveys, data validation and prescreening. We report a deployment aimed at employing voice-based, telephone services to conduct automated, structured interviews of low-literate users and to advertise relevant development-related services to them. Survey calls were placed to 67,000 vocational training recipients to validate their phone numbers and to find out their current job status. Of these, 45,500 answered these calls and 11,500 (25%) responded to the survey questions. Manually conducted follow-up interviews found more than 70% of the survey results to be consistent and also revealed the impact of phone sharing (among family members), call timing, simplicity of interface and surveyor-participant interpretation mismatch regarding certain survey questions on participant involvement and the validity of survey results. The paper discusses the use of IVR to collect information, possible system design considerations and factors affecting the accuracy of gathered information.

Routine early age child immunization is one of the most cost-effective public health interventions. The use of Information and Communication Technology (ICT) tools such as Immunization Information Systems (IIS) to improve efficiency of vaccination programs has shown mixed but encouraging results in terms of success. The objective of this paper is to present evidence of Evaccs -- a successfully deployed smartphone based vaccinator monitoring app, discuss the need to create a smartphone enabled IIS (called Har Zindagi -- every life matters) that can store digital records of every child, discuss various design and implementation features of Har Zindagi's android application, and present findings of the usability testing performed on the Har Zindagi android app. Given that the vaccinators are non tech-savvy, and the real estate on a smartphone is limited, this application was particularly designed to allow easy record entry process, and smoothen the workflow. This paper builds upon previous work on user interface design for low-literate users, and identifies techniques to iteratively design interfaces with government employees, who may be uncomfortable with giving usability feedback due to fear of repercussions or might have different field reality when compared to their supervisors and policy makers.

Thousands of lives are lost every year in developing countries for failing to detect epidemics early because of the lack of real-time disease surveillance data. We present results from a large-scale deployment of a telephone triage service as a basis for dengue forecasting in Pakistan. Our system uses statistical analysis of dengue-related phone calls to accurately forecast suspected dengue cases 2 to 3 weeks ahead of time at a subcity level (correlation of up to 0.93). Our system has been operational at scale in Pakistan for the past 3 years and has received more than 300,000 phone calls. The predictions from our system are widely disseminated to public health officials and form a critical part of active government strategies for dengue containment. Our work is the first to demonstrate, with significant empirical evidence, that an accurate, location-specific disease forecasting system can be built using analysis of call volume data from a public health hotline.

People with little or no reading abilities may not be able to read important information such as: instructions on medicine, warning sign boards, employment/property affidavits, government announcements in emergencies like viral diseases and storm alerts. This reading disability is further compounded when there is no literate around to explain meaning of the displayed information. In this paper, we present SpeakMyText - a platform which facilitates collaboration between reading-illiterates and volunteer literates to promote learning. SpeakMyText's mobile application enables a user to share an image containing text with a volunteer-translator who could then record and share-back its audio translation. The platform is specifically designed for non-literate users with several easy-to-use features like auto-signup; auto-login; multilingual graphical interface, 2-click interface to upload image and other similar features. This paper details its functionality and initial evaluation on a group of 60 reading-illiterates of different age groups and professions. System evaluation reveals promising results; more than 70 % of the non-literate/semi-literate users were able to easily access its basic functionality.

Illiteracy is one of the biggest development challenges, especially in the developing regions. There are 785M adult illiterates in the world; one in every five people has little or no basic reading skills. Illiteracy poses the following challenges: It limits the ability to understand essential information, it increases unemployment, poverty and it has a negative impact on health. In this study, we present VillageApps -- a framework to educate underprivileged communities in their mother tongue. The paper details the platform, its functionality, and its initial evaluation on a group of 30 school-aged children. Our framework consists of a web and a mobile application; the web application provides an interface to upload content and record its page by page audio translation; the mobile application provides an interface to view each page and simultaneously listen to its audio translation.

Natural disasters are, unfortunately, a fundamental part of living on Planet Earth. Earthquakes, floods, tornadoes, hurricanes, and other events will continue to test the strength of the infrastructure modern society relies on, such as communication equipment like cellular networks. In this work, we propose The Rescue Base Station (RBS) a drop-in, solar power compatible, open-source GSM communication system for the scenarios where a large-scale calamity disrupts traditional modes of communication. The system operates using asynchronously connected autonomous nodes and gathers useful information from users, eventually synchronizing this data across the network using distributed network protocols. It connects people through conventional GSM services allowing calls, SMS and smart phone features when available. The networks also provides a series of services for use during a disaster, such as intelligent call routing, attribute based search on different characteristics (name, occupation and blood group), voicemail services, SMS broadcast alerts, and emergency short-codes, through which a victim can contact available doctors, fire fighters, police and rescue workers.

We have been developing techniques for spreading telephone-based services to low-literate people in the developing world, bypassing the need for explicit user training. We achieve this by using entertainment as a viral conduit to spread and popularize development related voice-based services. Polly, our telephone-based voice manipulation and forwarding system, has been in continuous operation in Pakistan since May 2012. In this poster, we show the geographical spread of Polly over the initial four months of its deployment. We then describe our attempts at reducing our operating costs by shifting some of them to users, and the impact this had on user behavior, demonstrated via randomized control trials and by the usage of landline vs. mobile phones.

We have been developing techniques for spreading telephone-based services to low-literate people in the developing world, bypassing the need for explicit user training. We achieve this by using entertainment as a viral conduit to spread and popularize development related voice-based services. Polly, our telephone-based voice manipulation and forwarding system, has been in continuous operation in Pakistan since May 2012. In this poster, we show the geographical spread of Polly over the initial four months of its deployment. We then describe our attempts at reducing our operating costs by shifting some of them to users, and the impact this had on user behavior, demonstrated via randomized control trials and by the usage of landline vs. mobile phones.