Antenatal help, Antibiotic Resistance, and HIV Screening
Antenatal help, Antibiotic Resistance, and HIV Screening
Diseases and disorders tend to affect complex systems in different ways: understanding motivations, systems, and economics is key to getting healthcare to work out.
This week's newsletter is a mix of geopolitics, COVID-19, the economics of screening and finally, the economics of antibiotic resistance. I selected four papers this week. The first paper talks about the link between COVID-19 and geopolitical risk, finding that a heavy COVID-19 burden leads to increased geopolitical risk for countries. The second and third papers examine giving mothers antenatal care in the Niger and screening for HIV in Australia respectively. Finally, the last paper looks at the load antibiotic resistance may be placing on China's GDP.
COVID-19 and Geopolitics
A paper by Wang et. al. delves into the question of whether there is any causality between the spread of COVID-19 in a country and the geopolitical risk it faces. This seemed like a very interesting question to explore: I haven't seen any other analyses done in this manner, and especially not of COVID-19. The authors correlated the geopolitical risk with new COVID-19 cases per million and new deaths per million. The Geopolitical Risk is measured by an index described in a paper by Caldara and Iacoviello. The authors describe it as:
The authors search the archives of 11 international newspapers Boston Globe, Chicago Tribune, Daily Telegraph, Financial Times, Globe and Mail, Guardian, Los Angeles Times, New York Times, Times, Wall Street Journal, and Washington Post. The authors introduce the index by calculating the news related to all news articles related to geopolitical risks. The calculation is the basis of the data at the monthly frequency.
The authors created linear models and used the cross-section dependence test and the Granger non-causality test to check causality. The results were as you'd expect: geopolitical risk seems to be affected by new COVID-19 infections and deaths. The geopolitical risk index of a country is higher the more affected it is.
Links between antenatal care attendance and out of pocket costs
Ouedraogo et. al. examine the economics of antenatal care in Zinger, Niger. It had been seen that neonatal mortality went down from 54 deaths per 1000 live births to 26 deaths per 1000 live births between 1990 - 2007. One of the reasons this might have happened is because pregnant women and children under 5 years of age are exempted from healthcare costs. However, this does not translate to reduced maternal mortality, which remains stubbornly high at 556 per 100,000 in 2016 despite the free healthcare package including antenatal care, caesarean sections, and the treatment of gynaecological cancers. According to the authors:
For the routine ANC (antenatal care), the official exemption includes governmentally covered costs for the antenatal health booklet, consultations, intermittent preventive malaria treatment with sulfadoxine-pyrimethamine, iron folic acid (IFA) supplements, laboratory tests (glucose, albumin and infections), ultrasounds and consumable items necessary for the provision of these services. Prior to 2016, the World Health Organization (WHO) recommended at least four ANC visits for uncomplicated pregnancies with the first ANC visit occurring before the 12th week of gestation, the second visit around 26 weeks, the third around 32 weeks and the fourth between 36 and 38 weeks of gestation.
The primary reason this is done is to establish social contact with the mother and child and reduce both antenatal and post-partum complications for the mother and the child. In addition, previous studies in Ethiopia, Tanzania, Bangladesh and Pakistan have shown that higher out-of-pocket costs and greater travel time have been correlated with decreased maternal health seeking. In lieu of this, the authors had three aims:
Assess out-of-pocket costs for pregnant women attending antenatal care (ANC)
Estimate time spent to attend ANC and the opportunity cost of this time
See the affect of the above on antenatal care attendance
In order to do this, the authors looked at rural communities in their selected area. 18 Intermediate Health Centres (IHCs) were chosen out of convenience. Approximately 77 women were chosen per IHC. Since each IHC serves multiple villages, the authors tried to ensure that the participants were selected from multiple villages as well. The authors looked at ANC attendance based on gestational age, out-of-pocket costs, time spent for an ANC visit, opportunity cost, and they controlled for socio-economic status, food security and dietary diversity.
The authors were able to cover 92 villages in their selected region. They found that:
75% of the women they surveyed reported going for an ANC visit.
The women who were attending were more likely to have begun attending in the hot season (as compared to the rainy season), or had attended previously for another pregnancy
The women attending had, on average, more formal education than the country's average and also tended to be from non-farmer families
A majority of women sought ANC for the first time in their second trimester
Most women walked to their ANC centre and spent less than a day attending their session
The median opportunity cost reported was between $0.08 - $0.57
Most women saw out-of-pocket costs during the first visit, but very few reported any such costs subsequently. The median out-of-pocket charge was around $0.38 - $0.57
There also turned out to be a positive correlation between having delivered in a health facility during a previous pregnancy and seeking antenatal care. Women who had received an insecticide-treated-net or food during the visit also tended to come back for more visits.
But the most bizzare result in this paper was that women who spent money to receive antenatal care (had out-of-pocket costs) were more likely to have attended all their required ANC sessions. This goes against what has been seen in other countries and merits further investigation.
Comparison of HIV testing regimes
A paper by Williams et. al. sets out to compare the costs of three different regimes of HIV testing, namely conventional testing, parallel testing and point-of-care testing. This study was performed in Australia, which has some fairly intimidating targets. The HIV policy in the state basically aims to achieve 90-90-90 targets. They wish to diagnose 90% of all people who have HIV in the country, get 90% of them into anti-retroviral therapy, and achieve an undetectable viral load in 90% of them.
In Brisbane, where this study was conducted, the conventional method is an ELISA screen followed by a confirmatory Western Blot. The point-of-care (POC) method is the Direct HIV Combo (DHC) Assay in the form of an HIV self-test, and the parallel method is when an ELISA screen and a DHC Assay are performed simultaneously by an appropriately trained professional. The conventional method is generally seen in hospitals and clinics and is extremely accurate. However, the confirmatory Western Blot requires the patient to come in for a second visit. The parallel method has the advantage of using two screening tests and thus being more accurate as well as being performed in one patient visit. The POC test is the least accurate, but it can be performed at home.
The authors realised that conventional testing hs extremely expensive and the main cost is that of the medical staff. The use of volunteer nurses in this position reduces the cost to a third. Parallel testing reduces costs further because there are no follow-on visits. And finally, POC testing is the cheapest. The authors suggest that the use of POC tests might be the most appropriate here because the incidence of HIV was low enough in the population that a less efficient screening method was fairly cost-effective.
There are some major questions which come to mind at this conclusion. Since the authors don't describe the rate of false-positives when using POC tests, one wonders at the cost the confirmatory testing of these false positives would generate.
The Economic Burden of Antibiotic Resistance
Zhen et. al. take a look at the economic burden of antibiotic resistance as measured in China. They examined the effects of antibiotic resistance on hospital mortality, length of stay, and costs. According to the authors:
China was the second largest consumer of antibiotics in 2010 in the globe. In primary care facilities, 52.9% of outpatient prescriptions and 77.5% of inpatient prescriptions contained antibiotics, of which, only 39.4% and 24.6% were considered appropriate respectively. Among BRICS countries (Brazil, Russia, India, China, and South Africa), more than 57.0% of the increase in antibiotic consumption in hospital occurred in China between 2000 and 2010.
China is now leading the world in terms of antibiotic resistant bacterial strains. In the EU and the EEA, antibiotic resistance's costs were seen to be between 1.1 to 1.5 billion Euros. China's costs might prove to be even bigger.
In order to get the costs, the authors collected data from 3 sites in the Zhejiang Province and one in the Shandong Province. They performed a retrospective analysis.
In this study, we included patients with infection or colonisation caused by S. aureus, E. faecalis, E. faecium, E. coli, K. pneumonia, P. aeruginosa, and A. baumannii. We classified the infection or colonisation cases into susceptible episodes and resistant episodes (including resistant and intermediate isolates) based on the susceptibility test results for the patient specimens.
They defined Single Drug Resistance (SDR) as resistance to at least one antibiotic in one or two antibiotic categories, and Multiple Drig Resistance as resistance to antibiotics in three or more categories.
The economic costs of patients suffering from antibiotic resistance were obtained by multiplying the number of such patients with the average medical cost of a typical patient in a Chinese hospital.
The authors estimated that around 27% of all patients in hospitals had some form of antibiotic resistance and cost China around $77 billion, the same figure as that for the USA.
However there are some limitations in this study which the authors also acknowledge. The first is that the economic costs might not have been estimated properly because the hospitals chosen by the authors may not be representative of actual costs in China. The second is that this study only estimates the effect of antibiotic resistance in hospitals, but antibiotic resistance tends to be felt outside hospitals and in the wider community as well. Finally, the study does not estimate the costs of antibiotic resistance upon those who get colonised by antibiotic resistant bacteria but have not been infected by them.