by Dr. Nita Bharti

Movement and Health

Human movement and human health:

pathogen transmission and access to health care

 
Sunrise in Etengua, Namibia

Sunrise in Etengua, Namibia

We can’t separate studies of human health from studies of human populations.

We study the links between human health, human movement, and the environment

Current research topics: Measles, cholera, Ebola, SARS-CoV-2, access to health care, environmental drivers of movement, biases in measures of human movement

Movement is a critical element of human contact and connectivity, strongly influenced by environmental elements. Together, these factors determine pathogen transmission. We work to measure human movement to understand pathogen transmission and access to health care, particularly in areas where understudied contact patterns have limited the reach of public health interventions. Limited data or biased data on the distribution and abundance of human populations can undermine disease management efforts and access to health care, which ultimately increases health inequities.

A schematic of population dynamics for seasonally mobile populations. In agriculturally driven economies, such as Niger, population density, measles transmission, and access to health care simultaneously increase during the dry season as urban popul…

A schematic of population dynamics for seasonally mobile populations. In agriculturally driven economies, such as Niger, population density, measles transmission, and access to health care simultaneously increase during the dry season as urban populations grow. These populations decline during the rainy season, leading to decreased measles transmission as well as reduced access to health care and measles prevention. From Bharti et al 2016 Nature Scientific Reports.

It’s impossible to vaccinate a population adequately without knowing the size of that population.

bharti+slides+v2.jpg

Populations change over years, seasons, and weeks. Sometimes, they change regularly or predictably, which can help inform vaccination efforts. Our work measures these changes and quantifies how predictable they are to help close gaps in vaccination coverage. Our work in this area is primarily in Niger and Namibia.

Presentation1.jpg

We use many different data sources to measure the spatiotemporal dynamics of the distribution and abundance of human populations. For example, we can use use serial satellite images of anthropogenic light to measure seasonal fluctuations in human populations.

Nighttime lights and urban populations: Annual seasonal fluctuations of brightness across each of five cities in Niger and Nigeria. The top plot for each city in Niger shows the estimated measles transmission curves for each city in Niger on a scale of 0 (center) to 2 (perimeter) by month (January to December) from measles case reports from 1995-2005 (citations 4,18); data unavailable for Katsina, Nigeria. Each pixel in the animation reflects the local maximum of the quantified brightness value from DMSP-OLS satellite images at the time indicated by transmission plot. This nighttime lights animation, was created in D3.js (https://d3js.org/) by Patrick Dudas. Basemap: Map tiles by Carto (https://carto.com/), under CC BY 3.0, data by OpenStreetMap, under ODbL. Bharti et al 2018 Nature Scientific Data.

Nighttime lights and urban populations: Annual seasonal fluctuations of brightness across each of five cities in Niger and Nigeria. The top plot for each city in Niger shows the estimated measles transmission curves for each city in Niger on a scale of 0 (center) to 2 (perimeter) by month (January to December) from measles case reports from 1995-2005 (citations 4,18); data unavailable for Katsina, Nigeria. Each pixel in the animation reflects the local maximum of the quantified brightness value from DMSP-OLS satellite images at the time indicated by transmission plot. This nighttime lights animation, was created in D3.js (https://d3js.org/) by Patrick Dudas. Basemap: Map tiles by Carto (https://carto.com/), under CC BY 3.0, data by OpenStreetMap, under ODbL. Bharti et al 2018 Nature Scientific Data.

 

There are many data sources for information on human population sizes and there is a lot of disagreement between them. This creates uncertainty for vaccination programs, for example, when calculating how to achieve ~92% coverage, to break local chains of measles transmission.

(A) Point estimates of coverage of reinforcement activities in the city of Niamey, Niger from survey responses (left, black) and as calculated from doses distributed and city population size estimates from MSF, MoH, and the UN (left to right, faded …

(A) Point estimates of coverage of reinforcement activities in the city of Niamey, Niger from survey responses (left, black) and as calculated from doses distributed and city population size estimates from MSF, MoH, and the UN (left to right, faded points). Bright points and CI: Estimated coverage of reinforcement activities with CI including model estimates from posterior distribution of population flux using city population size estimates (bright points and lines). (B) Above: reported daily measles cases in Niamey. Below: estimated population fluxes of each commune by calendar day calculated from model. Vertical dashed line indicates start of reactive immunization campaign. Central solid lines indicate estimates for population flux based on posterior mean; shaded polygons indicate prediction intervals for flux based on central 95% of posterior distribution. From Bharti et al 2016 Nature Scientific Reports.

Desert in Niger just outside of Niamey

Desert in Niger just outside of Niamey

We have also applied these approaches to understand COVID-19 transmission in the US and measure interactions within and between populations to estimate the impact of behavioral interventions on disease transmission.

Relevant publications:

Small, M., Lennon, R., Dziak, J., Smith, R., Sommerville, G., Bharti, N. (2022) College Students' COVID-19 Vaccine Beliefs and Intentions: Implications for Interventions. Journal of American College Health; accepted. Preprint available on MedrXiv https://doi.org/10.1101/2021.05.28.21258008

Smith, R., Small, M., Bharti, N., DeMatte, S., Lennon, R, Ferrari, M., and the Data4Action Research Group. (2022) Normative influences and COVID-19 mitigation among college students: Processes, person-centered implications, and antibody results. Health Communication https://doi.org/10.1080/10410236.2022.2049047

Bharti, N., Lambert, B.
, Exten, C., Faust, C., Ferrari, M., Robinson, A. (2022) Large university with high COVID-19 incidence did not increase risk to non-student population. Scientific Reports 12, 3313. https://doi.org/10.1038/s41598-022-07155-x

Faust, C., Lambert, B., Kochenour, C., Robinson, A., Bharti, N. (2021) Passive surveillance assesses compliance with COVID-19 behavioural restrictions in a rural US county. Epidemiology and Infection, 149, E211. https://doi.org/10.1017/S0950268821002107

Hazel, A., Meeks, G., Bharti, N., Jakurama, J., Matundu, J., Jones, J. (2021) Opportunities and constraints in women’s resource security amid climate change: A case study of arid-living Namibian agro-pastoralists. Accepted American Journal of Human Biology.

Tao, Y., Hite, J., Lafftery, K., Earn, D.,* Bharti, N.* (2021) Transient disease dynamics across ecological scales. Theoretical Ecology. (*authors contributed equally) https://doi.org/10.1007/s12080-021-00514-w

Bharti, N. (2021) Linking Human Behaviors and Infectious Diseases. PNAS https://doi.org/10.1073/pnas.2101345118

Tejas S. Athni, Marta S. Shocket, Lisa I. Couper, Nicole Nova, Iain R. Caldwell, Jamie M. Caldwell, Jasmine N. Childress, Marissa L. Childs, Giulio A. De Leo, Devin Kirk, Andrew J. MacDonald, Kathryn Olivarius, David G. Pickel, Steven O. Roberts, Olivia C. Winokur, Hillary S. Young, Julian Cheng, Elizabeth A. Grant, Patrick M. Kurzner, Saw Kyaw, Bradford J. Lin, Ricardo C. López, Diba S. Massihpour, Erica C. Olsen, Maggie Roache, Angie Ruiz, Emily A. Schultz, Muskan Shafat, Rebecca L. Spencer, Nita Bharti *, Erin A. Mordecai * (2021) The influence of vector-borne disease on human history: socio-ecological mechanisms. Ecology Letters. 24(3) (* joint senior and corresponding authors), DOI: 10.1111/ele.13675

Blake, A., Djibo, A., Guindo, O., Bharti, N. (2020) Investigating persistent measles dynamics in Niger and associations with rainfall. J. R. Soc. Interface. 17(169), doi: https://doi.org/10.1098/rsif.2020.0480

Bharti, N. (2020) Controlling the coronavirus narrative. Science. 365(6505), DOI: 10.1126/science.abd3662

Bharti, N., Tatem, A. (2018) Fluctuations in anthropogenic nighttime lights from satellite imagery for five cities in Niger and Nigeria. Scientific Data 5:108256, doi: https://doi.org/10.1038/sdata.2018.256
open access reprint ScholarSphere open access data and code

Bharti, N., Djibo, A., Tatem, AJ, Grenfell, BT, Ferrari, MJ. (2016) Measuring populations to improve vaccination coverage. Scientific Reports 6:34541, doi: 10.1038/srep34541
open access reprint

Etengua, Namibia

Etengua, Namibia

Funding sources for this work:

NSF RAPID:DEB-2202872 Measuring uptake, persistence, and impact of behavioral interventions on respiratory viruses, 2022-2023.

Bill and Melinda Gates Foundation, 2020-2021.

COVID seed fund program 2020-2021 from Huck Institute of Life Sciences and The Institute for Computation and Data Sciences at Penn State University

Health and Environment seed fund from the Huck Institute 2017-2018

Data to Insight / Data to Innovation seed fund from the Huck Institute 2015-2016

Branco Weiss - Society in Science Fellowship 2012-2018

Otjitanda landing.gif