Mapping poverty using mobile phone and satellite data

Poverty is one of the most important determinants of adverse health outcomes globally, a major cause of societal instability and one of the largest causes of lost human potential. Traditional approaches to measuring and targeting poverty rely heavily on census data, which in most low- and middle-income countries (LMICs) are unavailable or out-of-date. Alternate measures are needed to comp- lement and update estimates between censuses. This study demonstrates how public and private data sources that are commonly available for LMICs can be used to provide novel insight into the spatial distribution of poverty. We evalu- ate the relative value of modelling three traditional poverty measures using aggregate data from mobile operators and widely available geospatial data. Taken together, models combining these data sources providethebest predictive power (highest r 2 ¼ 0.78) and lowest error, but generally models employing mobile data only yield comparable results, offering the potential to measure poverty more frequently and at finer granularity. Stratifying models into urban and rural areas highlights the advantage of using mobile data in urban areas and different data in different contexts. The findings indicate the possibility to estimate and continually monitor poverty rates at high spatial resolution in countries with limited capacity to support traditional methods of datacollection

Barriers of attendance to dog rabies static point vaccination clinics in Blantyre, Malawi

<div><p>Rabies is a devastating yet preventable disease that causes around 59,000 human deaths annually. Almost all human rabies cases are caused by bites from rabies-infected dogs. A large proportion of these cases occur in Sub Saharan Africa (SSA). Annual vaccination of at least 70% of the dog population is recommended by the World Health Organisation in order to eliminate rabies. However, achieving such high vaccination coverage has proven challenging, especially in low resource settings. Despite being logistically and economically more feasible than door-to-door approaches, static point (SP) vaccination campaigns often suffer from low attendance and therefore result in low vaccination coverage. Here, we investigated the barriers to attendance at SP offering free rabies vaccinations for dogs in Blantyre, Malawi. We analysed data for 22,924 dogs from a city-wide vaccination campaign in combination with GIS and household questionnaire data using multivariable logistic regression and distance estimation techniques. We found that distance plays a crucial role in SP attendance (i.e. for every km closer the odds of attending a SP point are 3.3 times higher) and that very few people are willing to travel more than 1.5 km to bring their dog for vaccination. Additionally, we found that dogs from areas with higher proportions of people living in poverty are more likely to be presented for vaccination (ORs 1.58-2.22). Furthermore, puppies (OR 0.26), pregnant or lactating female dogs (OR 0.60) are less likely to be presented for vaccination. Owners also reported that they did not attend an SP because they were not aware of the campaign (27%) or they could not handle their dog (19%). Our findings will inform the design of future rabies vaccination programmes in SSA which may lead to improved vaccination coverage achieved by SP alone.</p></div

Exposure and risk factors to Coxiella burnetii, spotted fever group and typhus group rickettsiae, and Bartonella henselae among volunteer blood donors in Namibia

Background: The role of pathogen-mediated febrile illness in sub-Saharan Africa is receiving more attention, especially in Southern Africa where four countries (including Namibia) are actively working to eliminate malaria. With a high concentration of livestock and high rates of companion animal ownership, the influence of zoonotic bacterial diseases as causes of febrile illness in Namibia remains unknown.Methodology/Principal Findings: The aim of the study was to evaluate exposure to Coxiella burnetii, spotted fever and typhus group rickettsiae, and Bartonella henselae using IFA and ELISA (IgG) in serum collected from 319 volunteer blood donors identified by the Blood Transfusion Service of Namibia (NAMBTS). Serum samples were linked to a basic questionnaire to identify possible risk factors. The majority of the participants (64.8%) had extensive exposure to rural areas or farms. Results indicated a C. burnetii prevalence of 26.1% (screening titre 1:16), and prevalence rates of 11.9% and 14.9% (screening titre 1:100) for spotted fever group and typhus group rickettsiae, respectively. There was a significant spatial association between C. burnetii exposure and place of residence in southern Namibia (P0.012), especially cattle (P>0.006), were also significantly associated with C. burnetii exposure. Males were significantly more likely than females to have been exposed to spotted fever (P<0.013) and typhus (P<0.011) group rickettsiae. Three (2.9%) samples were positive for B. henselae possibly indicating low levels of exposure to a pathogen never reported in Namibia.Conclusions/Significance: These results indicate that Namibians are exposed to pathogenic fever-causing bacteria, most of which have flea or tick vectors/reservoirs. The epidemiology of febrile illnesses in Namibia needs further evaluation in order to develop comprehensive local diagnostic and treatment algorithms.Peer reviewedEntomology and Plant Patholog

Routine data for malaria morbidity estimation in Africa: challenges and prospects

Background The burden of malaria in sub-Saharan Africa remains challenging to measure relying on epidemiological modelling to evaluate the impact of investments and providing an in-depth analysis of progress and trends in malaria response globally. In malaria-endemic countries of Africa, there is increasing use of routine surveillance data to define national strategic targets, estimate malaria case burdens and measure control progress to identify financing priorities. Existing research focuses mainly on the strengths of these data with less emphasis on existing challenges and opportunities presented. Conclusion Here we define the current imperfections common to routine malaria morbidity data at national levels and offer prospects into their future use to reflect changing disease burdens.</p

Insecticide-treated net distribution in Western Kenya: impacts related to COVID-19 and health worker strikes

We examined the impact of coronavirus disease (COVID) mitigation, supply and distribution interruptions on the delivery of long-lasting insecticide-treated nets (LLINs) in Western Kenya. The median monthly distribution of LLINs declined during COVID mitigation strategies (March-July 2020) and during the health worker strikes (December 2020-February 2021). Recovery periods followed initial declines, indicative of a 'catching up' on missed routine distribution. Mass community campaigns were delayed by 10&#xA0;months. These observations offer encouragement for routine net distribution resilience, but complete interruptions of planned mass distributions require alternate strategies during pandemics

Model building and assessment of the impact of covariates for disease prevalence mapping in low-resource settings: to explain and to predict

This paper provides statistical guidance on the development and application of model-based geostatistical methods for disease prevalence mapping. We illustrate the different stages of the analysis, from exploratory analysis to spatial prediction of prevalence, through a case study on malaria mapping in Tanzania. Throughout the paper, we distinguish between predictive modelling, whose main focus is on maximizing the predictive accuracy of the model, and explanatory modelling, where greater emphasis is placed on understanding the relationships between the health outcome and risk factors. We demonstrate that these two paradigms can result in different modelling choices. We also propose a simple approach for detecting over-fitting based on inspection of the correlation matrix of the estimators of the regression coefficients. To enhance the interpretability of geostatistical models, we introduce the concept of domain effects in order to assist variable selection and model validation. The statistical ideas and principles illustrated here in the specific context of disease prevalence mapping are more widely applicable to any regression model for the analysis of epidemiological outcomes but are particularly relevant to geostatistical models, for which the separation between fixed and random effects can be ambiguous

Fever prevalence and management among three rural communities in the North West Zone, Somalia.

Between March and August 2008 we undertook 2 cross-sectional surveys among 1375 residents of 3 randomly selected villages in the district of Gebiley in the North-West Zone, Somalia. We investigated for the presence of malaria infection and the period prevalence of self-reported fever 14 days prior to both surveys. All blood samples examined were negative for both species of Plasmodium. The period prevalence of 14-day fevers was 4.8% in March and 0.6% in August; the majority of fevers (84.4%) were associated with other symptoms including cough, running nose and sore throat; 48/64 cases had resolved by the day of interview (mean duration 5.4 days). Only 18 (37.5%) fever cases were managed at a formal health care facility: 7 within 24 hours and 10 within 24-72 hours of onset. None of the fevers were investigated for malaria; they were treated with antibiotics, antipyretics and vitamins

The receptive versus current risks of Plasmodium falciparum transmission in northern Namibia: implications for elimination.

Background: Countries aiming for malaria elimination need to define their malariogenic potential, of which measures of both receptive and current transmission are major components. As Namibia pursues malaria elimination, the importation risks due to cross-border human population movements with higher risk neighboring countries has been identified as a major challenge. Here we used historical and contemporary Plasmodium falciparum prevalence data for Namibia to estimate receptive and current levels of malaria risk in nine northern regions. We explore the potential of these risk maps to support decision-making for malaria elimination in Namibia. Methods: Age-corrected geocoded community P. falciparum rate PfPR2-10 data from the period 1967–1992 (n = 3,260) and 2009 (n = 120) were modeled separately within a Bayesian model-based geostatistical (MBG) framework. A full Bayesian space-time MBG model was implemented using the 1967–1992 data to make predictions for every five years from 1969 to 1989. These maps were used to compute the maximum mean PfPR2-10 at 5 x 5 km locations in the northern regions of Namibia to estimate receptivity. A separate spatial Bayesian MBG was fitted to the 2009 data to predict current risk of malaria at similar spatial resolution. Using a high-resolution population map for Namibia, population at risk by receptive and current endemicity by region and population adjusted PfPR2-10 by health district were computed. Validations of predictions were undertaken separately for the historical and current risk models. Results: Highest receptive risks were observed in the northern regions of Caprivi, Kavango and Ohangwena along the border with Angola and Zambia. Relative to the receptive risks, over 90% of the 1.4 million people across the nine regions of northern Namibia appear to have transitioned to a lower endemic class by 2009. The biggest transition appeared to have occurred in areas of highest receptive risks. Of the 23 health districts, 12 had receptive PAPfPR2-10 risks of 5% to 18% and accounted for 57% of the population in the north. Current PAPfPR2-10 risks was largely &lt;5% across the study area. Conclusions: The comparison of receptive and current malaria risks in the northern regions of Namibia show health districts that are most at risk of importation due to their proximity to the relatively higher transmission northern neighbouring countries, higher population and modeled receptivity. These health districts should be prioritized as the cross-border control initiatives are rolled out.</p