Meningitis Project Annual Report
Submitted to XXXXX, google.org
October 2011
From Rajul Pandya, University Corporation for Atmospheric Research (UCAR)
Representing the work of Abudulai Adams-Forgor, Patricia Akweongo (NHRC), and
Abraham Hodgson (Navrongo Health Research Centre – NHRC); Vanja Dukic
(University of Colorado); Katie Dickinson, Mary Hayden, and Tom Hopson (National
Center for Atmospheric Research – NCAR); Benjamin Lamptey (Regional Maritime
University, Ghana); Roberto Mera and Fred Semazzi (North Carolina State
University – NCSU); Jennie Rice (Pacific Northwest National Laboratory); Madeleine
Thomson and Sylwia Trazka (International Research Institute for Climate and
Society - IRI); Tom Yoksas (UCAR/Unidata); Raj Pandya (UCAR)
12 Months from Agreement Date (October 2009)
In addition to the activities reported against this milestone in previous reports, we
have made additional progress in the last year.
12.1: Local Partnerships and Formal Agreements Established
a) Expanded partnership in Africa
As documented in the previous reports, we have subcontracts with Navrongo Health
Research Centre (NHRC) to collaboratively perform the socio-economic and
knowledge, attitudes and practices survey outlined in Milestones 24.1, 32.1, and
36.1. In addition, Dr. Patricia Akweongo is now affiliated with the University of
Ghana and Dr. Abraham Hodgson has become Director of Research for Ghana Health
Service, which as allowed informal connections to both of those resources.
b) Progress on work with Regional Maritime University
Although we have a subcontract with Dr. Benjamin Lamptey at the Royal Maritime
University (RMU), his work on the project has been hampered by poor internet
connectivity, difficulty setting-up the 4-node workstation necessary to perform
necessary model simulations, and inability to locate a graduate student to
participate in the research. In August of 2011, Lamptey spent two months in
residence at NCAR focused on the training necessary to make the computer
modeling operational. In addition, his contribution to the project was redesigned to
be less-dependent on bandwidth – he will now focus on the reanalysis of the
weather during the 2010 meningitis season which will be used to evaluate the
benefit of improved prediction (as described in deliverable 36.1). If time permits,
he will extend his analysis to look at the likely impact of climate on meningitis by
simulating a future years weather projection (and probability of meningitis) based
on IPCC projections, as well as participate in a new initiative to investigate the
UCAR Meningitis-Weather Project Annual Report To Google, October 2011
Page 1 of 11
impacts of assimiliating a new measurements of atmospheric vertically-integrated
water vapor (COSMIC program) into numerical weather prediction models to
improve the latter’s forecasting skill. Lamptey has also hired a Master’s student.
12.2 Existing Meningitis and weather data located, archived and documented
No new historical data has been added to the project since the previous written
report (Oct 2010).
12.3 Demonstrated Weather-Meningitis Links
In addition to the work previously documented, we have additional evidence for a
robust weather-meningitis link, and have preliminary evidence suggesting a link
between air-quality and meningitis, described below.
a) The role of weather assessed through population-level modeling of meningitis spread
Dr. Tom Hopson has collaborated with Dr. Vanja Dukic to model the transmission of
meningitis using a differential equation-based epidemiological compartmental
model of a known disease and physical insight into meningitis transmission. Using
the data described in 12.2, they performed a statistical analysis to test the model for
correlation with meteorological variables. They showed that relative humidity,
vapor pressure, and northeasterly wind all show positive correlation with current
and future cases of meningitis, as compared to simple historical persistence.
Their SCIS (susceptible-colonized-infected-susceptible) model is based on a
continuous Methicillin-resistant Staphylococcus aureus (MRSA) model, but
simplified and tested based on the following assumptions:

The number of cases of disease is small compared to overall population

District population is constant,

Carriage (the number of people who harbor the bacteria but don’t have the
disease) is proportional to population,

The proximity to neighboring districts with cases of meningitis influences the
chances of having a case

The same mechanisms determine transmission and infection across the
breadth of the meningitis belt

The disease cycle is less than two weeks

Weather in the centroid of the district is representative of district-wide
weather
In the figures below we show some of the results of this study. In the left panel of
Figure 1 we show the World Health Organization districts across part of the
meningitis belt, with the meningitis epidemic likelihood dependence on relative
humidity shown in the rightmost panel. In Figure 2 below, we show how a one-week
ahead average relative humidity (RH) ensemble mean forecast over the meningitis
belt in Spring of 2010 (top panel) translates into a 3-week ahead meningitis forecast
across the belt (bottom panel).
UCAR Meningitis-Weather Project Annual Report To Google, October 2011
Page 2 of 11
b) The role of weather assessed through generalize additive modeling of meningitis
incidence
To examine how robust the relationship is between relative humidity and water
vapor with meningitis incidence, Dr. Mary Hayden and Dukic developed a statistical
model – a generalized additive model – to robustly examine the effect of weather
variables on meningitis incidence over time. This model adjusts for time-varying
confounding processes that co-vary with the weather variables of interest (in
particular, relative humidity) and which also may impact meningitis spread. Regular
seasonal human behavior patterns fall in this category (e.g. harvest-worker
migration.) Their analysis on 11 years of Navrongo incidence revealed substantial
stability in the relationship of meningitis to several weather variables, under
various modeling assumptions, and a wide range of degree of confounding
adjustment. Temperature and relative humidity were among the variables most
persistently related to meningitis incidence, in addition to the amount of CO in the
air due to burning biomass (fires).
12.4 Ensemble derived forecasts for meningitis management developed and verified
This deliverable is complete, as documented in previous reports. Since then,
Hopson has negotiated the use of more accurate forecast products from the World
Meteorological Organization (instead of using 2-day delayed ensemble forecasts, he
is able to use the forecasts as soon as they are available) and is evaluating the
improvement in forecast this enables.
12.5 Protocol and technology for health-weather communication defined
This was meant to be a logistical and technical infrastructure that would collect,
quality control and make available health and weather related data so that a
decision support system could be reliably operated. Unlike meteorological data,
which are readily and currently and available due to long-standing international
agreements and processes, health data has proved difficult to locate and
incorporate in any ongoing way. Even our MERIT colleagues at the World Health
Organization don’t always have up-to-date or comprehensive health data.
Given that, we’ve decided to build our DSS using a numerical model that relates case
trends to weather variables without requiring initial case data. However, for those
users willing to enter their case data, we will be able to provide a more accurate
forecast and ask them to contribute that data to an archive for general use. In this
way, we hope to incentivize the contribution of health data to our DSS and to our
partner efforts.
24 Months from Agreement Date (October 2010)
24.1 & 24.2 Decision support system for Meningitis management developed, including
forecast products.
This pending milestone, concerning the deployment and dissemination of a decision
support system (DSS), is the one requiring the most work. The system is being
developed to be easy to use and provide actionable information to health-decision
UCAR Meningitis-Weather Project Annual Report To Google, October 2011
Page 3 of 11
makers while also allowing access to underlying data and models. In order for this
to happen, the DSS is being designed to include underlying epidemiological data
(Section 12.2) and meteorological forecasts (Section 12.4), analysis and
visualization tools, and the mathematical models (Section 12.3) to predict future
meningitis outbreak risk thresholds from current climate conditions and data, as
well as time-evolving estimated meningitis outbreak end-of-season dates, critical for
optimal vaccine allocation decision-making. Our goal is to work with an African
partner to build this decision support system in Africa. As a precursor to this we
are developing a working prototype here in UCAR while soliciting feedback from
the World Health Organization.
After three years in the Google.org project, we’ve built all the necessary precursors.
 Unidata has the visualization, analysis and data management tools that can
support the DSS.
 Our team has documented the relationship between meningitis and several
meteorological variables, with an especially strong signal on humidity.
Further, this relationship can be used to predict future cases of meningitis
 We’ve developed the technical and logistical infrastructure necessary to
forecast those relevant meteorological variables and built relationships with
relevant forecast centers to access those data in a regular way.
This is the deliverable that we will focus most on in the coming year. Hopson has
worked with Mr. Tom Yoksas and others to create a precursor pilot website that
provides the forecasts for the current season based on weather variables and
projects the end of the season. (Please see
http://www.cbp.ucar.edu/activities/google_project/index.php). Another DSS
feature under development is web functionality that will allow users to incorporate
their local health information, which will then be passed to a more site-specific
model, to produce a more refined local forecast of epidemiological conditions. This
functionality will also allow us to record (with permission of the user) these local
health data into a data base, which itself will be accessible to other regional and
international stakeholders in real-time. Based on this prototype, we intend to
engage with stakeholders in the region and internationally to continue to build and
refine a usable decision support system over the upcoming year.
Within a few weeks, we intend to submit to Google a detailed plan and budget that
would reprogram the remaining funds to this deliverable.
24.3 Surveillance protocol arrangements set up and new health data collected
Existing surveillance in the K-N district included the routine identification and
laboratory confirmation of new cases of meningitis, at the rate of a hundred or so
new cases per season. The quality of the surveillance has been steady through the
last 10 years, and there was little need to extend the current protocol in our study
area, Navrongo.
UCAR Meningitis-Weather Project Annual Report To Google, October 2011
Page 4 of 11
Dukic has used this opportunity to develop IP surveillance tools that could be used
for wider Ghana, and possibly extended to the entire meningitis Belt, with the help
of WHO. IP Surveillance is based on Google Insights for Search, and preliminary
results reveal high degree of correlation between Navrongo reported incidence and
several meningitis-related search terms. Predictive validation is currently ongoing.
In November 2011, Dr. Rajul Pandya and Hodgson will attend the next meeting of
the MERIT steering committee, and one of the topics of discussion will be the
sharing of data among project participants and public health stakeholders and
decision makers. We hope to emerge with a protocol, or set of protocols, that will
allow us to outline next steps in refining the decision-support tool.
24.4 Draft economic evaluation complete
As outlined in previous reports, this milestone is completed.
32 Months from Agreement Date (August 2010)
32.1 Baseline data collected to inform economic evaluation
This milestone is completed. We have performed Cost-of-Illness surveys on 74
households in the K-N district who have experienced meningitis. Ms. Jennie Rice and
Dr. Jeff Lazo drafted the instrument; the household level survey was refined, pretested and conducted by Akweongo, Hayden and the team at the Navrongo Health
Research Centre.
32.2 An extensible weather and Meningitis data-archive and a distribution protocol
for integrating health and weather data complete
Please see Milestone 12.5. As stated there, the regular collection and sharing of
health data has proven to be beyond the scale of our ability or connections, and even
challenges our WMO partners. As such, our archive will be launched with only the
historical data we already have permission to use, but it will incentivize the
collection of additional data via its link to the DSS.
36 Months from Agreement Date (October 2011)
36.1 Preliminary economic evaluation of the decision support system
As mentioned in 36.1, quantitative Cost of Illness (COI) interviews were conducted
with 74 cases and the cost of illness was computed from patients’ answers to
questions about direct medical costs, direct non-medical costs and productivity lost
due to meningitis. Analysis by Maxwell Dalaba and Timothy Akwine, supervised by
Patricia Akweongo, suggest that the average household cost of treating meningitis
case was GH₵232 (US$156) per case, which is higher than the average income of
farmers GH₵130 (US$87) in the district. Much of the total cost of meningitis was
from productivity lost (60%) and the average number of days lost due to meningitis
was 29 days. In addition, the average cost when meningitis sequalae (such as
hearing, neurological and vision problems) occurred was GH₵ 1,257 (US$843) per
case.
UCAR Meningitis-Weather Project Annual Report To Google, October 2011
Page 5 of 11
Additional costs are born by the healthcare infrastructure, and we are working with
Adams-Forgor, who has left NHRC to serve as the director of Navrongo’s War
Memorial Hospital (the only hospital in the K-N district), to obtain an estimate of
these costs.
To determine the potential benefit of the DSS, we plan to retrospectively forecast a
past meningitis season, apply the DSS to that season, and compare the results of
those decisions to the results of decisions actually made. Lamptey is performing the
necessary forecasts for that analysis. We will also estimate the cost of maintaining
the DSS, and extrapolate the impact of the DSS in K-N to estimate the impact of the
DSS across the entire belt.
36.1 Full report, for non-technical audiences.
A full report is pending the completion of the project. A very brief overview of the
project, intended for non-technical audiences, is available at
http://prezi.com/6qf0djihwl0r/weather-forecasts-and-applications-in-africa-challenges-value-and-communication/
In addition, some material about the project intended for a public audience
UCAR’s Press Release
http://www2.ucar.edu/news/899/health-and-weather-ucar-weather-forecasts-aim-reduce-african-meningitis-epidemics
A story on Voice of America
http://www.voanews.com/learningenglish/home/a-23-2008-11-24-voa1-83139962.html
An article from the Daily Camera
http://www.voanews.com/learningenglish/home/a-23-2008-11-24-voa1-83139962.html
36.1 Demonstrated dissemination in Ghana and throughout western and eastern
Africa of strategies and lessons
 The UCAR team has participated in several MERIT meetings, in Ethiopia and
Niger, which have introduced the project to public health services in both
locations. MERIT also provides a forum to engage with the World Health
Organization and the Health-Climate Foundation, which have reach across Africa.
 Lamptey is a member of the World Meteorological Organization’s Thorpex-Africa
steering committee, and has ensured that the google.org-funded project is
included in their guiding documents as an example of the application of
meteorological data. This document is the product of deliberations that include
representatives of every African Weather Service, and
 The UCAR team has presented the project quite widely in the international
geoscience community including several presentations at international
geoscience conferences.
 This work has been and will be presented at the meeting of the Annual Meeting
of the American Society of Tropical Medicine and Hygiene, which, in spite of its
name, is the premier international meeting for the field of tropical medicine.
Additionally, the work will be presented at the Annual Meeting of the American
Meteorological Society in early 2012.
UCAR Meningitis-Weather Project Annual Report To Google, October 2011
Page 6 of 11
Additional Accomplishments, not part of the original scope or work
A.1 A survey of Knowledge, Attitudes, and Practices
Knowledge, attitudes and practices (KAP) regarding meningitis transmission are
poorly understood and likely to show considerable variation across the meningitis
belt. With encouragement from MERIT, NHRC and UCAR decided to document KAP
as part of our cost-of-illness survey. Akweongo, Hodgson, and Hayden designed the
survey and NHRC staff, led by Mr. Maxwell Dalaba, conducted quantitative
interviews with 74 cases (people who had contracted meningitis between 2008 and
the present) and 148 controls (age, gender and location matched group made up of
people who had not had meningitis after 2008).
The preliminary results showed:
 High knowledge about stiffness of waist or neck as a symptom of meningitis by
both cases and controls, but cases were more likely to mention other, real early
symptoms (high body temperature, vomiting, severe headache, loss of the
appetite) than controls. Both cases and controls recognized meningitis as a
serious disease requiring immediate treatment. Together, these findings suggest
that education about early symptoms might lead to earlier health-care seeking
behavior and subsequent treatment for meningitis with improved health
outcomes.
 No significant differences between the cases and controls with regards to
perception of the causes of meningitis: heat was the most common cause
mentioned by both cases and controls. Additionally, seventy percent of both
cases and controls mentioned hot and dry periods as the time of the year
meningitis is most severe.
 Seasonal Migration can confer protective benefit. Many rural men travel south
during the dry season to seek farm-related work. Because these men leave the
meningitis region and often do not return until planting in the north begins with
the start of the rainy season, they are protected from meningitis. However, these
same men are at greater risk if they need to return to northern Ghana during the
meningitis season (for funerals, for example) as they will have missed the
vaccination campaign.
 More wealthy individuals often miss the vaccination campaigns, which are aimed
at poorer, rural areas. This fact, combined with increased mobility, meant that
many wealthier individuals showed increased risk of meningitis compared to
less wealthy peers.
A.1 An analysis of cook stove emissions
As part of the KAP/COI survey monitoring in February of 2011, our team was
able to leverage funds from other sources to allow us test air quality at several
homes in K-N district, both with and without improved clean cook stoves. This effort,
led by UCAR scientist Christine Weidinmyer and collaborators at the University of
Colorado, suggests that air-quality in the region is poor in the dry season, and that
the use of clean cook stoves can decrease exposure to indoor smoke resulting from
traditional cooking practices. This preliminary work is the basis for a collaborative
UCAR Meningitis-Weather Project Annual Report To Google, October 2011
Page 7 of 11
proposal with Hodgson, Akweongo and others that will explore the link between air
quality and respiratory illness and the potential impact of scaled-up clean cook
stove use.
A.2 A characterization of the variation in relative humidity across West Africa
during the dry season
As part of the effort to determine the variability of relative humidity, given its
impact on meningitis, Hopson and Warner collaborated with Dr. Mark Seefeldt on a
study to examine the variation of relative humidity across West Africa during the dry
season evaluated using the NASA MERRA dataset and the method of self-organizing
maps. The patterns in relative humidity were analyzed in terms of frequency of each
pattern as well as the sequencing from one pattern to the next. The variations in relative
humidity are characterized sub-annually for individual years from 1979 to 2009 as well
as decadally over the entire 30-year duration of dry seasons in West Africa. The
progression from relatively moist patterns to relatively dry patterns and back to the moist
patterns over the course of the dry season corresponds to the northward and then
southward migration of the intertropical convergence zone. The results indicate distinctly
different frequency and sequencing of relative humidity patterns from year to year. The
year-to-year changes in relative humidity patterns are gradual. There is some indication
of a larger, possibly decadal, pattern to the year-to-year changes in the variation of
relative humidity over the course of the dry season.
A.3 An analysis of proximity to water bodies and the impact on meningitis cases
As part of the effort to examine the impacts of relative humidity meningitis, Hopson
and Hayden supervised Kristen McCormack, a local high school student through
UCAR’s HIRO program, to investigate the relationship between proximity to water
bodies and suppression of meningitis cases. The study was carried using meningitis
case data from the Navrango Health and Research Centre in proximity to Tono Dam,
located in the Kassena/Nankana District of northern Ghana. Results are shown
immediately below where we see a possible linear relationship between distance
from water and increased meningitis vulnerability.
UCAR Meningitis-Weather Project Annual Report To Google, October 2011
Page 8 of 11
UCAR Meningitis-Weather Project Annual Report To Google, October 2011
Page 9 of 11
Figure 1: World Health Organization districts across part of the meningitis belt
shown in the left-most panel, with the meningitis epidemic (here, as defined by 10
cases/100,000) likelihood dependence on relative humidity shown in the rightmost
panel.
UCAR Meningitis-Weather Project Annual Report To Google, October 2011
Page 10 of 11
Figure 2: Top panel shows the one-week ahead average relative humidity (RH)
ensemble mean forecast over the meningitis belt, initialized on March 27, 2011. The
bottom panel shows how this RH forecast converts to a 3-week ahead meningitis
forecast across the belt, represented as probability of exceeding 10 cases/100,000
reported over that week.
UCAR Meningitis-Weather Project Annual Report To Google, October 2011
Page 11 of 11